Google Cloud MCP Server
Connects to Google Cloud services to provide context and tools for interacting with Google Cloud resources, including logging, monitoring, Spanner, and more.
Allows executing SQL queries against Spanner databases, listing available databases and tables, and exploring database schema.
Integration in development for interacting with Google Cloud Storage services.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Google Cloud MCP Servershow me logs from project my-app-prod-123 from the last hour with severity ERROR"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Google Cloud MCP Server
A Model Context Protocol server that connects to Google Cloud services to provide context and tools for interacting with your Google Cloud resources.
Services
Supported Google Cloud services:
Billing
Manage and analyse Google Cloud billing with cost optimisation insights:
Tools: gcp-billing-list-accounts, gcp-billing-get-account-details, gcp-billing-list-projects, gcp-billing-get-project-info, gcp-billing-list-services, gcp-billing-list-skus, gcp-billing-analyse-costs, gcp-billing-detect-anomalies, gcp-billing-cost-recommendations, gcp-billing-service-breakdown
Example prompts:
"Show me all my billing accounts"
"Analyse costs for project my-app-prod-123 for the last 30 days"
"Generate cost recommendations for billing account billingAccounts/123456-789ABC-DEF012"
"Check for billing anomalies in project my-ecommerce-456"
Error Reporting
Monitor and analyse application errors with automated investigation and remediation suggestions:
Tools: gcp-error-reporting-list-groups, gcp-error-reporting-get-group-details, gcp-error-reporting-analyse-trends
Example prompts:
"Show me error groups from project my-webapp-prod-789 for the last hour"
"Get details for error group projects/my-app-123/groups/xyz789"
"Analyse error trends for service my-api in project analytics-prod-456"
IAM
Query and analyse IAM policies and permissions:
Tools: gcp-iam-get-project-policy, gcp-iam-test-project-permissions, gcp-iam-test-resource-permissions, gcp-iam-validate-deployment-permissions, gcp-iam-list-deployment-services, gcp-iam-analyse-permission-gaps
Example prompts:
"Get IAM policy for project my-webapp-prod-123"
"Test if I have storage.buckets.create permission on project data-lake-456"
"Check deployment permissions for Cloud Run in project microservices-789"
"Analyse permission gaps for deploying to GKE cluster in project k8s-prod-321"
Logging
Query and filter log entries from Google Cloud Logging:
Tools: gcp-logging-query-logs, gcp-logging-query-time-range, gcp-logging-search-comprehensive
Example prompts:
"Show me logs from project my-app-prod-123 from the last hour with severity ERROR"
"Search for logs containing 'timeout' from service my-api in project backend-456"
"Query logs for resource type gce_instance in project compute-prod-789"
Spanner
Interact with Google Cloud Spanner databases:
Tools: gcp-spanner-execute-query, gcp-spanner-list-tables, gcp-spanner-list-instances, gcp-spanner-list-databases, gcp-spanner-query-natural-language, gcp-spanner-query-count
Example prompts:
"List all databases in Spanner instance my-instance in project ecommerce-prod-123"
"Execute SQL: SELECT COUNT(*) FROM users in database user-db in project my-app-456"
"Show me table structure for orders in database inventory-db in project retail-789"
Monitoring
Retrieve and analyse metrics from Google Cloud Monitoring:
Tools: gcp-monitoring-query-metrics, gcp-monitoring-list-metric-types, gcp-monitoring-query-natural-language
Example prompts:
"Show me CPU utilisation metrics for project web-app-prod-123 for the last 6 hours"
"List available metric types for Compute Engine in project infrastructure-456"
"Query memory usage for instances in project backend-services-789"
Profiler
Analyse application performance with Google Cloud Profiler:
Tools: gcp-profiler-list-profiles, gcp-profiler-analyse-performance, gcp-profiler-compare-trends
Example prompts:
"List CPU profiles from project my-java-app-123 for the last 24 hours"
"Analyse performance bottlenecks in service my-api in project backend-prod-456"
"Compare heap profiles for deployment v1.2 vs v1.3 in project performance-test-789"
Trace
Analyse distributed traces from Google Cloud Trace:
Tools: gcp-trace-get-trace, gcp-trace-list-traces, gcp-trace-find-from-logs, gcp-trace-query-natural-language
Example prompts:
"Get trace details for ID abc123def456 in project distributed-app-789"
"Show me failed traces from project microservices-prod-123 from the last hour"
"Find logs related to trace xyz789 in project web-backend-456"
"Query traces for service checkout-api in project ecommerce-prod-321"
Related MCP server: GCP MCP
Quick Start
Once configured, you can interact with Google Cloud services using natural language:
"What are my current billing costs for project my-webapp-prod-123?"
"Show me errors from project ecommerce-api-456 in the last hour"
"Check if I have permission to deploy to Cloud Run in project microservices-789"
"Find logs containing 'database timeout' from project backend-prod-321 yesterday"
"List Spanner databases in instance prod-db for project data-store-654"
"What's the CPU usage of Compute Engine instances in project infrastructure-987?"Authentication
This server supports two methods of authentication with Google Cloud:
Service Account Key File (Recommended): Set the
GOOGLE_APPLICATION_CREDENTIALSenvironment variable to the path of your service account key file. This is the standard Google Cloud authentication method.Environment Variables: Set
GOOGLE_CLIENT_EMAILandGOOGLE_PRIVATE_KEYenvironment variables directly. This is useful for environments where storing a key file is not practical.
The server will also use the GOOGLE_CLOUD_PROJECT environment variable if set, otherwise it will attempt to determine the project ID from the authentication credentials.
Installation
# Clone the repository
git clone https://github.com/krzko/google-cloud-mcp.git
cd google-cloud-mcp
# Install dependencies
pnpm install
# Build
pnpm buildAuthenticate to Google Cloud:
gcloud auth application-default loginConfigure the mcpServers in your client:
{
"mcpServers": {
"google-cloud-mcp": {
"command": "node",
"args": [
"/Users/foo/code/google-cloud-mcp/dist/index.js"
],
"env": {
"GOOGLE_APPLICATION_CREDENTIALS": "/Users/foo/.config/gcloud/application_default_credentials.json"
}
}
}
}Development
Starting the server
# Build the project
pnpm build
# Start the server
pnpm startDevelopment mode
# Build the project
pnpm build
# Start the server and inspector
npx -y @modelcontextprotocol/inspector node dist/index.jsTroubleshooting
Server Timeout Issues
If you encounter timeout issues when running the server with Smithery, try the following:
Enable debug logging by setting
debug: truein your configurationEnsure
lazyAuth: trueis set to defer authentication until it's actually neededEnsure your credentials file is accessible and valid
Check the logs for any error messages
Important: Authentication is still required for operation, but with lazy loading enabled, the server will start immediately and authenticate when needed rather than during initialization.
Authentication Issues
The server supports two methods of authentication:
Service Account Key File: Set
GOOGLE_APPLICATION_CREDENTIALSenvironment variable to the path of your service account key fileEnvironment Variables: Set
GOOGLE_CLIENT_EMAILandGOOGLE_PRIVATE_KEYenvironment variables
If you're having authentication issues, make sure:
Your service account has the necessary permissions
The key file is properly formatted and accessible
Environment variables are correctly set
Available Tools
40 toolsgcp-billing-analyse-costsAnalyse Billing CostsC
Perform detailed cost analysis with trends and insights for Google Cloud billing data
| Name | Required | Description | Default |
|---|---|---|---|
| billingAccountName | Yes | Billing account name (e.g., 'billingAccounts/123456-789ABC-DEF012') | |
| startDate | Yes | Start date for cost analysis (ISO format: YYYY-MM-DD) | |
| endDate | Yes | End date for cost analysis (ISO format: YYYY-MM-DD) | |
| projectId | No | Optional project ID to filter costs | |
| serviceId | No | Optional service ID to filter costs | |
| groupBy | No | Group costs by project, service, SKU, or time | service |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It only mentions 'analysis' without specifying whether it is read-only, what permissions are needed, or any side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single, clear sentence with no filler words. Efficiently conveys the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema exists, and the description does not explain what the tool returns (e.g., aggregated costs, time series). Missing details on output format and behavioral context make it incomplete for a 6-parameter analysis tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema covers all parameters with descriptions, achieving 100% coverage. The description does not add additional meaning beyond what is in the schema, so baseline score applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Perform detailed cost analysis with trends and insights', which clearly indicates a cost analysis tool. It distinguishes from sibling billing tools like recommendations or anomalies, though 'insights' is somewhat vague.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives such as gcp-billing-cost-recommendations or gcp-billing-detect-anomalies. The description lacks explicit context for appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-billing-cost-recommendationsGenerate Cost RecommendationsB
Generate cost optimisation recommendations with potential savings for Google Cloud billing
| Name | Required | Description | Default |
|---|---|---|---|
| billingAccountName | Yes | Billing account name (e.g., 'billingAccounts/123456-789ABC-DEF012') | |
| projectId | No | Optional project ID to filter recommendations | |
| minSavingsAmount | No | Minimum savings amount to include in recommendations | |
| priority | No | Filter recommendations by priority level | all |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It only states the purpose and mentions potential savings, but does not disclose whether the operation is read-only, what errors may occur, or any side effects. The agent is left guessing about the behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 13 words, efficiently conveying the core function without waste. It is well-structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 4 parameters, no output schema, and no annotations, the description is insufficient. It does not explain the return format (e.g., list of recommendations with savings amounts), any constraints, or how filtering parameters interact. A more complete description is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema description coverage is 100%, so the schema already documents each parameter. The description adds no additional value beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'generate' and the resource 'cost optimisation recommendations with potential savings' for Google Cloud billing. It distinguishes itself from sibling tools like analyse-costs and detect-anomalies by focusing specifically on recommendations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for generating cost saving recommendations but provides no explicit guidance on when to use over alternatives or when not to use. No exclusions or context about prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-billing-detect-anomaliesDetect Cost AnomaliesB
Detect unusual cost patterns and spending anomalies in Google Cloud billing data
| Name | Required | Description | Default |
|---|---|---|---|
| billingAccountName | Yes | Billing account name (e.g., 'billingAccounts/123456-789ABC-DEF012') | |
| lookbackDays | No | Number of days to look back for comparison (7-90) | |
| thresholdPercentage | No | Percentage threshold for anomaly detection (10-500%) | |
| projectId | No | Optional project ID to filter anomalies |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must convey behavioral traits. It does not disclose whether the tool is read-only, what side effects exist, or any authorization requirements. The description is insufficient to inform an agent about operational implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. There is no use of bullet points, sections, or front-loaded key information. It meets minimum readability but is not optimally organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description fails to explain what the tool returns, how anomalies are defined, or any constraints. The description is minimal and does not provide enough context for an agent to use the tool effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, meaning all four parameters have descriptions. The tool description does not add any parameter-specific context beyond the schema. Baseline is 3 as the schema already handles parameter semantics adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Detect' and identifies the resource as 'unusual cost patterns and spending anomalies in Google Cloud billing data'. It clearly distinguishes from sibling tools like 'gcp-billing-analyse-costs' and 'gcp-billing-cost-recommendations' which focus on analysis and recommendations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or scenarios where other tools might be more appropriate. Usage context is entirely implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-billing-get-account-detailsGet Billing Account DetailsA
Retrieve detailed information about a specific Google Cloud billing account
| Name | Required | Description | Default |
|---|---|---|---|
| billingAccountName | Yes | Billing account name (e.g., 'billingAccounts/123456-789ABC-DEF012') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full burden. The description only states 'retrieve', implying read-only, but does not disclose auth requirements, rate limits, or other behavioral traits beyond a minimal verb.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence with no superfluous words. Information is front-loaded with the action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter read tool without output schema, the description is adequate but lacks behavioral context (e.g., idempotency, authorization) that would be expected given no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the schema already describes the parameter. The description does not add additional semantics or format hints beyond what is in the schema, meeting the baseline for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly specifies the action ('retrieve detailed information') and the resource ('specific Google Cloud billing account'), distinguishing it from sibling tools like list-accounts or list-projects.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives (e.g., list-accounts). Usage is implied but not stated, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-billing-get-project-infoGet Project Billing InformationB
Retrieve billing configuration and status for a Google Cloud project
| Name | Required | Description | Default |
|---|---|---|---|
| projectId | No | Project ID (defaults to current project from state manager) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only implies a read operation without disclosing any behavioral traits such as permissions needed, rate limits, or what exactly 'billing configuration and status' includes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, concise, and front-loaded with the action and resource. Every word is necessary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is too brief. It does not describe the return structure, potential error conditions, or what constitutes 'billing configuration', leaving an agent with insufficient context for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, and the description does not add any meaning beyond the schema. The baseline is 3 because the schema already documents the parameter adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Retrieve', the resource 'billing configuration and status', and the scope 'for a Google Cloud project'. It distinguishes this read-only tool from sibling billing analysis or account details tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description mentions that the projectId defaults to the current project from state manager, providing some context. However, it does not specify when to use this tool versus other billing tools like get-account-details or list-projects, nor when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-billing-list-accountsList Billing AccountsA
List all Google Cloud billing accounts accessible to the user
| Name | Required | Description | Default |
|---|---|---|---|
| pageSize | No | Maximum number of billing accounts to return (1-50) | |
| pageToken | No | Token for pagination to get next page of results | |
| filter | No | Optional filter for billing accounts (e.g., 'open=true') |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose important behavioral traits like pagination, rate limits, or what happens if no accounts are found. The schema includes pageSize and pageToken, but the description omits any mention of pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no redundant words. It is front-loaded and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with three optional parameters and no output schema, the description is mostly adequate. It could mention pagination or the shape of the response, but it provides sufficient context for an agent to understand the tool's purpose.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (all three parameters have descriptions). The tool description adds no additional parameter information beyond the schema, so it meets the baseline of 3 for high coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and the resource 'Google Cloud billing accounts', with scope 'accessible to the user'. It is distinct from sibling tools like gcp-billing-get-account-details which target a single account.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when you need all billing accounts but provides no explicit guidance on when to use alternatives or when not to use. It does not mention sibling tools or exclude scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-billing-list-projectsList Billing Account ProjectsB
List all projects associated with a specific Google Cloud billing account
| Name | Required | Description | Default |
|---|---|---|---|
| billingAccountName | Yes | Billing account name (e.g., 'billingAccounts/123456-789ABC-DEF012') | |
| pageSize | No | Maximum number of projects to return (1-200) | |
| pageToken | No | Token for pagination to get next page of results |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It only states that it lists projects, omitting important details like pagination behavior (though schema includes pageToken), return format, authentication needs, rate limits, and error handling for invalid billing accounts.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that is front-loaded and contains no fluff. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the basic purpose but fails to explain return values or error cases. Since there is no output schema, the description should have mentioned what fields are returned for each project. It also doesn't address the full context of the 3-parameter inputs beyond the required one.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema; it only mentions the billing account name implicitly. The other parameters (pageSize, pageToken) are not described in the description, but they are well-documented in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'List' and the resource 'projects associated with a specific Google Cloud billing account'. It effectively distinguishes from sibling tools like `gcp-billing-list-accounts` (lists accounts) and `gcp-billing-get-project-info` (gets details of a specific project).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lacks any guidance on when to use this tool versus alternatives, such as when to list projects under a billing account vs. analyzing costs or getting project details. No prerequisites, exclusions, or context for appropriate use are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-billing-list-servicesList Google Cloud ServicesC
List all available Google Cloud services for billing and cost analysis
| Name | Required | Description | Default |
|---|---|---|---|
| pageSize | No | Maximum number of services to return (1-200) | |
| pageToken | No | Token for pagination to get next page of results |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must fully communicate behavior. It does not mention pagination, required permissions, or whether results are scoped to a project/account.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, front-loaded with the key action 'list all'. It is concise but omits important details like pagination behavior.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description fails to explain pagination, return format, or prerequisites. For a simple list tool, this is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage; both pageSize and pageToken are documented with details. The description does not add extra parameter meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it lists Google Cloud services for billing and cost analysis. It is specific about verb and resource, but does not distinguish from sibling tools like gcp-billing-list-skus or gcp-billing-list-accounts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as gcp-billing-list-skus or gcp-billing-analyse-costs. The description lacks context for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-billing-list-skusList Service SKUsB
List all SKUs (Stock Keeping Units) and pricing information for a Google Cloud service
| Name | Required | Description | Default |
|---|---|---|---|
| serviceId | Yes | Google Cloud service ID (e.g., 'services/6F81-5844-456A') | |
| pageSize | No | Maximum number of SKUs to return (1-100) | |
| pageToken | No | Token for pagination to get next page of results | |
| currencyCode | No | Currency code for pricing information (default: USD) | USD |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden for behavioral disclosure. It states 'list' (implying read-only) but does not mention auth requirements, rate limits, or any side effects. The brevity leaves the agent uninformed about constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single clear sentence of 13 words with no redundant information. It is highly concise and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema, the description minimally states it returns 'SKUs and pricing information'. While adequate for a basic list, it could elaborate on the response structure or additional details for completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds no extra meaning beyond the schema; it does not explain how to use parameters like serviceId or pageSize.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the verb 'list' and the resource 'SKUs and pricing information', and it distinguishes from sibling tools like 'gcp-billing-list-services' by specifying it is for a particular Google Cloud service, implying the need for a service ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., other list tools), nor does it mention prerequisites, exclusions, or scenarios where another tool would be appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-billing-service-breakdownGet Service Cost BreakdownB
Get detailed cost breakdown by Google Cloud service with usage and SKU information
| Name | Required | Description | Default |
|---|---|---|---|
| billingAccountName | Yes | Billing account name (e.g., 'billingAccounts/123456-789ABC-DEF012') | |
| projectId | No | Optional project ID to filter costs | |
| timeRange | No | Time range for analysis (7d, 30d, 90d, 1y) | 30d |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must bear full weight for behavioral disclosure. It indicates the tool provides detailed breakdown including usage and SKU info, but does not mention read-only nature, pagination, or potential limitations. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, clear sentence with no unnecessary words. It front-loads the key action and resource, making it efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and moderate parameter count, the description could be more complete. It does not explain return format, error handling, or default behavior for optional parameters. Acceptable but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds that results include usage and SKU information, which is not in the schema, providing slight additional meaning beyond the parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves a cost breakdown by Google Cloud service with usage and SKU information. It effectively communicates the purpose but does not explicitly differentiate from sibling billing tools like gcp-billing-analyse-costs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, nor any prerequisites or exclusions. The description implies usage for service-level breakdown but lacks explicit when-to-use/when-not-to-use context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-error-reporting-analyse-trendsD
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-error-reporting-get-group-detailsD
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-error-reporting-list-groupsD
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-iam-analyse-permission-gapsAnalyse Permission GapsB
Compare current permissions against required permissions for specific operations and identify gaps
| Name | Required | Description | Default |
|---|---|---|---|
| project | No | Project ID (defaults to current project) | |
| requiredPermissions | Yes | List of permissions required for the intended operation | |
| operationDescription | No | Description of the operation being attempted (for context) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose all behavioral traits. It does not state whether the tool is read-only, what 'current permissions' means (project-level vs. resource-level), or whether it modifies anything. Essential details like output format and side effects are missing, leaving significant gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence that efficiently communicates the tool's core functionality with no extraneous words. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of an output schema, the description should explain return values (e.g., list of gaps, summary) and prerequisites like required IAM permissions to read policies. It does not provide these details, leaving the agent underinformed about the tool's results and dependencies.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage with clear explanations for each parameter. The description adds context by framing the purpose as comparing permissions, but does not significantly enhance parameter meaning beyond what the schema already provides. Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compares current permissions against required ones and identifies gaps, using specific verbs 'compare' and 'identify gaps'. It distinguishes itself from siblings like gcp-iam-get-project-policy (which retrieves policy) and gcp-iam-test-project-permissions (which tests specific permissions).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for permission gap analysis but provides no explicit guidance on when to use this tool over alternatives like gcp-iam-test-project-permissions or gcp-iam-test-resource-permissions. It does not mention when not to use it or provide context for choosing this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-iam-get-project-policyGet Project IAM PolicyB
Retrieve the IAM policy for a Google Cloud project
| Name | Required | Description | Default |
|---|---|---|---|
| project | No | Project ID (defaults to current project) | |
| requestedPolicyVersion | No | The policy format version (1, 2, or 3) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must carry the full behavioral burden. It only states 'retrieve,' implying read-only, but fails to mention required permissions, rate limits, or response details. This is insufficient for a mutation-free tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is efficient but lacks enough detail to be fully informative. It could be expanded without losing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema and no annotations, the description omits behavioral context like return structure and authentication needs. For a simple read tool this is borderline, but the lack of guidance and transparency makes it incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with descriptive fields (e.g., 'The policy format version'). The description adds no extra meaning beyond the schema, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Retrieve the IAM policy for a Google Cloud project' uses a specific verb ('retrieve') and resource ('IAM policy'), clearly stating the tool's purpose. It distinguishes itself from sibling tools like gcp-iam-analyse-permission-gaps, which are more analytical, through its naming and description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. Sibling tools like gcp-iam-analyse-permission-gaps exist, but the description offers no context or exclusion criteria, leaving the agent without usage decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-iam-list-deployment-servicesList Available Deployment ServicesA
List all GCP services with pre-defined deployment permission sets
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states a read-only listing operation, which is straightforward, but it does not disclose any potential limitations, authentication requirements, or response behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that communicates the core functionality without extraneous information. It is appropriately front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (no parameters, no output schema), the description is adequate but could be more informative. It does not explain what 'pre-defined deployment permission sets' are or what the output looks like.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has no parameters, so schema coverage is 100%. Per the baseline rule for 0 parameters, a score of 4 is appropriate since the description does not need to add parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list' and the resource 'GCP services with pre-defined deployment permission sets'. It differentiates from sibling tools like gcp-billing-list-services and other IAM tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool vs alternatives such as gcp-iam-validate-deployment-permissions or gcp-iam-get-project-policy. The description lacks any context about appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-iam-test-project-permissionsTest Project IAM PermissionsB
Test which permissions the current caller has on a Google Cloud project
| Name | Required | Description | Default |
|---|---|---|---|
| project | No | Project ID (defaults to current project) | |
| permissions | Yes | List of permissions to test (e.g., ["resourcemanager.projects.get", "compute.instances.list"]) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description should disclose behavioral traits. It implies a read-only operation but does not explicitly state it, nor does it mention authentication requirements, rate limits, or what happens when permissions are missing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that efficiently conveys the tool's purpose with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool, the description is adequate but lacks information about return values, error handling, and prerequisites like enabling the IAM API. It does not fully compensate for the missing output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters with descriptions, so the baseline is 3. The tool description adds no extra meaning beyond the schema's parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool tests which permissions the current caller has on a Google Cloud project, using a specific verb and resource, and distinguishes it from sibling tools like gcp-iam-test-resource-permissions which test at resource level.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives like gcp-iam-analyse-permission-gaps or gcp-iam-test-resource-permissions. The agent must infer from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-iam-test-resource-permissionsTest Resource-Specific IAM PermissionsB
Test which permissions the current caller has on specific Google Cloud resources
| Name | Required | Description | Default |
|---|---|---|---|
| resource | Yes | The full resource name (e.g., "projects/my-project/buckets/my-bucket", "projects/my-project/zones/us-central1-a/instances/my-instance") | |
| permissions | Yes | List of permissions to test on the resource |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It implies a read-only permission check with no side effects, which is adequate. However, it does not mention potential error conditions, response details, or whether the tool requires certain IAM roles to be callable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 12 words, front-loaded with the core action. Every word earns its place with no redundancy or filler. It is perfectly concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (two required parameters with clear descriptions, no output schema), the description sufficiently covers the purpose and expected inputs. It is complete for a straightforward permission-checking tool, though it could explicitly mention that the response lists which permissions are held.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add additional meaning beyond the schema; it paraphrases the parameters ('specific resources' for 'resource', 'which permissions' for 'permissions'). No examples or format clarifications are provided.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool tests which permissions the current caller has on specific Google Cloud resources. It is specific and uses a verb+resource structure. While it does not explicitly differentiate from the sibling gcp-iam-test-project-permissions, the resource-specific nature is evident from the title and description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives like gcp-iam-test-project-permissions. It lacks context on prerequisites, such as required roles, or scenarios where this tool is preferable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-iam-validate-deployment-permissionsValidate Deployment PermissionsC
Check if current caller has required permissions for deploying to common GCP services
| Name | Required | Description | Default |
|---|---|---|---|
| service | Yes | GCP service to validate (cloud-run, gke, compute-engine, cloud-functions, app-engine, cloud-storage, cloud-sql) | |
| project | No | Project ID (defaults to current project) | |
| includeOptional | No | Include optional permissions in the validation |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must fully disclose behavior. It only says 'Check', implying a read-only operation, but does not specify what the tool returns (e.g., boolean, list of missing permissions) or whether it makes any state changes. It lacks crucial details for safe invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is concise but lacks structure. It conveys the core purpose but omits any additional sentences that could add value without being verbose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no output schema, the description should explain the return value and how to interpret results. It does not, leaving the agent uncertain about the tool's output. The description is insufficient for a tool with 3 parameters and no annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage with descriptions for all three parameters. The description adds no additional meaning beyond the schema, so it meets the baseline but does not enhance understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool checks if the current caller has required permissions for deploying to common GCP services. It differentiates from siblings like gcp-iam-test-project-permissions by focusing on deployment context, though not explicitly contrasting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives (e.g., gcp-iam-analyse-permission-gaps, gcp-iam-test-project-permissions). No exclusions or prerequisites are mentioned, leaving the agent to infer usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-logging-query-logsQuery LogsC
Query Google Cloud Logs with custom filters. Searches across all payload types (text, JSON, proto) and metadata fields.
| Name | Required | Description | Default |
|---|---|---|---|
| filter | Yes | The filter to apply to logs (Cloud Logging query language) | |
| limit | No | Maximum number of log entries to return |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, and the description gives minimal behavioral context. It does not mention pagination, cost implications, or what happens with large result sets. The only extra info is 'searches across all payload types' which is nearly tautological.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-loading the primary action. No unnecessary words or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description is too brief. It does not explain return format, time range defaults, error handling, or any constraints on the search.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the description adds no additional meaning beyond the schema. It mentions 'custom filters' but does not elaborate on filter syntax or usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool queries Google Cloud Logs with custom filters across all payload types and metadata fields. However, it does not explicitly distinguish from sibling tools like gcp-logging-query-time-range or gcp-logging-search-comprehensive.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives (e.g., time-range query or comprehensive search). No prerequisites or context about appropriate use cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-logging-query-time-rangeQuery Logs by Time RangeC
Query Google Cloud Logs within a specific time range. Supports relative times (1h, 2d) and ISO timestamps.
| Name | Required | Description | Default |
|---|---|---|---|
| startTime | Yes | Start time in ISO format or relative time (e.g., "1h", "2d") | |
| endTime | No | End time in ISO format (defaults to now) | |
| filter | No | Additional filter criteria | |
| limit | No | Maximum number of log entries to return |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Only mentions input format support (relative times, ISO timestamps). Does not disclose other behaviors like pagination, rate limits, or what happens if query returns no results.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that front-load the purpose and key feature. No unnecessary words or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters and no output schema or annotations, the description is too brief. It lacks details on how to construct the filter, what logs are returned, or any special behaviors. More context is needed for complete understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% description coverage, already describing each parameter. The description adds a small clarification that the tool supports relative times and ISO timestamps, but this largely overlaps with the parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it queries Google Cloud Logs within a time range, with supported time formats. However, does not differentiate from sibling tools like gcp-logging-query-logs or gcp-logging-search-comprehensive, which may have overlapping functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. Lacks explicit context for when to choose this tool, e.g., when a simple time-range query is needed versus more complex searches.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-logging-search-comprehensiveComprehensive Log SearchC
Search across all log fields including textPayload, jsonPayload, protoPayload, labels, HTTP requests, and metadata. Provides maximum context.
| Name | Required | Description | Default |
|---|---|---|---|
| searchTerm | Yes | Term to search for across all payload types and fields | |
| timeRange | No | Time range to search (e.g., "1h", "24h", "7d") | 1h |
| severity | No | Minimum severity level to filter by | |
| resource | No | Resource type to filter by (e.g., "cloud_function", "gke_container") | |
| limit | No | Maximum number of log entries to return |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only states that the tool 'provides maximum context' but does not mention read-only nature, authentication requirements, rate limits, or response format. The behavioral impact is largely unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long and front-loads key information about searched fields. The second sentence is somewhat generic ('Provides maximum context') but not overly verbose. It earns its place but could be tighter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters and no output schema, the description is incomplete. It fails to explain return values, pagination behavior, error handling, or how 'maximum context' manifests. Without annotations, this gap leaves the agent guessing about the tool's full behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the input schema already documents all parameters thoroughly. The description adds minimal value beyond the schema—only listing some payload fields in prose. It does not explain parameter interactions or provide examples, warranting a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: searching across all log fields including specific types like textPayload and jsonPayload. It uses a specific verb ('search') and resource ('logs'), making the purpose clear. However, it does not explicitly distinguish itself from sibling tools like gcp-logging-query-logs, which might have narrower scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives (e.g., gcp-logging-query-logs for simpler queries). There is no mention of prerequisites, exclusions, or typical use cases, leaving the agent without direction for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-monitoring-list-metric-typesD
| Name | Required | Description | Default |
|---|---|---|---|
| filter | No | Simple search term (e.g., "spanner") or full filter expression (e.g., "metric.type = starts_with(\"spanner\")") | |
| pageSize | No | Maximum number of metric types to return | |
| timeout | No | Timeout in seconds for the request |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-monitoring-query-metricsD
| Name | Required | Description | Default |
|---|---|---|---|
| filter | Yes | The filter to apply to metrics | |
| startTime | Yes | Start time in ISO format or relative time (e.g., "1h", "2d") | |
| endTime | No | End time in ISO format (defaults to now) | |
| alignmentPeriod | No | Alignment period (e.g., "60s", "300s") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-monitoring-query-natural-languageD
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural language description of the query you want to execute | |
| startTime | No | Start time in ISO format or relative time (e.g., "1h", "2d") | |
| endTime | No | End time in ISO format (defaults to now) | |
| alignmentPeriod | No | Alignment period (e.g., "60s", "300s") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-profiler-analyse-performanceD
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-profiler-compare-trendsD
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-profiler-list-profilesD
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-spanner-execute-queryD
| Name | Required | Description | Default |
|---|---|---|---|
| sql | Yes | The SQL query to execute | |
| instanceId | No | Spanner instance ID (defaults to SPANNER_INSTANCE env var) | |
| databaseId | No | Spanner database ID (defaults to SPANNER_DATABASE env var) | |
| params | No | Query parameters |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-spanner-list-databasesD
| Name | Required | Description | Default |
|---|---|---|---|
| instanceId | Yes | Spanner instance ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-spanner-list-instancesD
| Name | Required | Description | Default |
|---|---|---|---|
| _dummy | No | Not used, just to ensure parameter compatibility |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-spanner-list-tablesD
| Name | Required | Description | Default |
|---|---|---|---|
| instanceId | No | Spanner instance ID (defaults to SPANNER_INSTANCE env var) | |
| databaseId | No | Spanner database ID (defaults to SPANNER_DATABASE env var) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-spanner-query-countD
| Name | Required | Description | Default |
|---|---|---|---|
| instanceId | No | Spanner instance ID (optional, if not provided will show all instances) | |
| databaseId | No | Spanner database ID (optional, if not provided will show all databases) | |
| queryType | No | Type of queries to count (ALL, READ, QUERY) | ALL |
| status | No | Status of queries to count (ALL, OK, ERROR) | ALL |
| startTime | No | Start time for the query (e.g., "1h", "2d", "30m") | 1h |
| endTime | No | End time for the query (defaults to now) | |
| alignmentPeriod | No | Alignment period for aggregating data points (e.g., "60s", "5m", "1h") | 60s |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-spanner-query-natural-languageD
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural language description of the query you want to execute | |
| instanceId | No | Spanner instance ID (defaults to SPANNER_INSTANCE env var) | |
| databaseId | No | Spanner database ID (defaults to SPANNER_DATABASE env var) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-trace-find-from-logsD
| Name | Required | Description | Default |
|---|---|---|---|
| projectId | No | Optional Google Cloud project ID | |
| filter | Yes | Filter for logs (e.g., "severity>=ERROR AND timestamp>"-1d"") | |
| limit | No | Maximum number of logs to check |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-trace-get-traceD
| Name | Required | Description | Default |
|---|---|---|---|
| traceId | Yes | The trace ID to retrieve | |
| projectId | No | Optional Google Cloud project ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-trace-list-tracesD
| Name | Required | Description | Default |
|---|---|---|---|
| projectId | No | Optional Google Cloud project ID | |
| filter | No | Optional filter for traces (e.g., "status.code != 0" for errors) | |
| limit | No | Maximum number of traces to return | |
| startTime | No | Start time in RFC3339 format (e.g., "2023-01-01T00:00:00Z") or relative time (e.g., "1h", "2d") |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-trace-query-natural-languageD
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Natural language query about traces (e.g., "Show me failed traces from the last hour") | |
| projectId | No | Optional Google Cloud project ID |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Tool has no description.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Tool has no description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool has no description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Tool has no description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Tool has no description.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Tool has no description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-utils-get-project-idGet Project IDA
Get the current Google Cloud project ID and recent project history
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the full burden. It states the output (current project ID and history) but omits details like the scope of 'recent history' or authentication requirements. It is adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly states the tool's purpose with no extraneous information. It is well-suited for quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no parameters and no output schema, the description covers the essential purpose. However, it could be enhanced by specifying the format of 'recent project history' to eliminate ambiguity. Still, it is largely sufficient for a simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters are defined, so schema coverage is 100%. The baseline for zero parameters is 4, and the description appropriately explains what the tool returns without needing parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'Get' and clearly specifies the resource: 'current Google Cloud project ID and recent project history'. It distinguishes from the sibling 'gcp-utils-set-project-id' by focusing on retrieval rather than mutation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for retrieving the active project context but provides no explicit guidance on when to use it versus alternative tools, such as those in billing or IAM. Given the simplicity, a moderate score is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
gcp-utils-set-project-idSet Project IDA
Set the default Google Cloud project ID to use for all operations
| Name | Required | Description | Default |
|---|---|---|---|
| project_id | Yes | The Google Cloud project ID to set as default |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description only states 'Set' without disclosing side effects, persistence, or error behavior. The agent gets minimal behavioral context beyond the fact that it is a mutation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 12-word sentence with no extraneous information, perfectly front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple setter tool with one parameter and no output schema, the description covers the essential purpose. However, it lacks context about error handling or validation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds no new meaning beyond what the schema already provides for the single required parameter. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool sets the default GCP project ID for all operations, with a specific verb and resource, distinguishing it from sibling tools like gcp-utils-get-project-id.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage as a prerequisite for other GCP operations but does not explicitly state when to use it or when not to, nor does it offer alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
40 tool updates
- First observed
gcp-billing-analyse-costs - First observed
gcp-billing-cost-recommendations - First observed
gcp-billing-detect-anomalies - First observed
gcp-billing-get-account-details - First observed
gcp-billing-get-project-info - First observed
gcp-billing-list-accounts - First observed
gcp-billing-list-projects - First observed
gcp-billing-list-services - First observed
gcp-billing-list-skus - First observed
gcp-billing-service-breakdown - First observed
gcp-error-reporting-analyse-trends - First observed
gcp-error-reporting-get-group-details - First observed
gcp-error-reporting-list-groups - First observed
gcp-iam-analyse-permission-gaps - First observed
gcp-iam-get-project-policy - First observed
gcp-iam-list-deployment-services - First observed
gcp-iam-test-project-permissions - First observed
gcp-iam-test-resource-permissions - First observed
gcp-iam-validate-deployment-permissions - First observed
gcp-logging-query-logs - First observed
gcp-logging-query-time-range - First observed
gcp-logging-search-comprehensive - First observed
gcp-monitoring-list-metric-types - First observed
gcp-monitoring-query-metrics - First observed
gcp-monitoring-query-natural-language - First observed
gcp-profiler-analyse-performance - First observed
gcp-profiler-compare-trends - First observed
gcp-profiler-list-profiles - First observed
gcp-spanner-execute-query - First observed
gcp-spanner-list-databases - First observed
gcp-spanner-list-instances - First observed
gcp-spanner-list-tables - First observed
gcp-spanner-query-count - First observed
gcp-spanner-query-natural-language - First observed
gcp-trace-find-from-logs - First observed
gcp-trace-get-trace - First observed
gcp-trace-list-traces - First observed
gcp-trace-query-natural-language - First observed
gcp-utils-get-project-id - First observed
gcp-utils-set-project-id
TDQS
Tools are separated by service prefix, but within services like logging and Spanner, multiple tools for querying logs or databases overlap in purpose. Additionally, many tools lack descriptions, increasing ambiguity.
All tools follow a consistent pattern: 'gcp-{service}-{action}-{noun}' in snake_case. For example, gcp-billing-list-accounts, gcp-iam-get-project-policy. No mixing of styles.
40 tools is high but not extreme for a multi-service server. However, several services have only 3 tools with missing descriptions, suggesting the count is inflated without full coverage.
Many services have significant gaps: error reporting, monitoring, profiler, and trace lack CRUD operations and detailed descriptions. Spanner is missing update/delete. Billing and logging are more complete, but overall surface is incomplete.
Maintenance
Resources
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Related MCP Connectors
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The Google GKE MCP server is a managed Model Context Protocol server that provides AI applications with tools to manage Google Kubernetes Engine (GKE) clusters and Kubernetes resources. It exposes a structured, discoverable interface that allows AI agents to interact with GKE and Kubernetes APIs, enabling them to inspect cluster configurations, retrieve Kubernetes resource YAMLs, monitor operations like cluster upgrades, diagnose issues, and optimize costs—all without needing to parse text output or use complex kubectl commands.
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A Model Context Protocol server for Wix AI tools
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