How do I use bearer-mcp-server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@bearer-mcp-server Run a diagnostic on the production API" 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.

bearer-mcp-server

by Shylendra

Overview Schema Related Servers Score Discussions

TypeScript

Hybrid

bearer-mcp-server

A production-style Model Context Protocol (MCP) server with bearer token authentication, written in TypeScript with the official @modelcontextprotocol/sdk.

It demonstrates all three core MCP primitives — tools, resources, and prompts — themed as a developer platform API with mock data (projects, deployments, API keys, metrics, logs, diagnostics).

Compatible with MCP protocol versions 2025-11-25 and 2026-07-28.

It supports two transports out of the box:

stdio — for desktop clients (Claude Desktop, MCP Inspector launching a subprocess). No auth.
Streamable HTTP — for HTTP-based clients, with session management and bearer token authentication.

What's inside

Tools (model-controlled actions)

Tool	Description
`echo`	Echoes text back — a connectivity and auth check.
`search_projects`	Search projects by name, language, status, or tags with pagination.
`get_project`	Get a single project by ID with full details including owner info.
`create_project`	Create a new project in the platform.
`deploy_service`	Trigger a deployment pipeline to a target environment.
`list_api_keys`	List API keys for a project (keys are masked).
`rotate_api_key`	Rotate (regenerate) an API key — full key shown only here.
`get_metrics`	Get 24-hour usage and performance metrics for a project. Returns structured output.
`search_logs`	Full-text search across simulated log entries with level/project filters.
`run_diagnostic`	Run a comprehensive health diagnostic on a project. Returns structured output.

Resources (application-controlled, read-only data)

URI	Description
`config://server`	Static JSON server config, version, auth mode, and feature flags.
`docs://api-reference`	Markdown API reference for the mock developer platform.
`projects://{id}`	Templated resource backed by mock project store (20+ projects), with listing.
`projects://{id}/metrics`	Metrics sub-resource for a project.
`users://{id}`	Templated user profile resource, with listing.
`status://system`	Live system status — services, regions, and active incidents.

Prompts (user-controlled message templates)

Prompt	Arguments	Description
`debug_deployment`	`projectName`, `errorMessage`, `environment`	Ask the model to diagnose a failed deployment.
`write_api_docs`	`endpoint`, `language`, `includeExamples`	Ask the model to generate API documentation.
`review_config`	`configType`, `configYaml`	Ask the model to review a configuration for security and correctness.
`incident_postmortem`	`service`, `severity`, `summary`, `duration`	Ask the model to draft a blameless postmortem.

Related MCP server: mock-mcp

Quick start

# 1. Install dependencies
npm install

# 2. Build the TypeScript
npm run build

# 3a. Run over Streamable HTTP (with bearer auth)
npm start

# 3b. ...or run over stdio for desktop clients
npm run start:stdio

Requires Node.js >= 18.

Development (no build step, auto-reload)

npm run dev:stdio   # stdio transport with tsx watch
npm run dev:http    # HTTP transport with tsx watch

Authentication

The HTTP transport requires a Bearer token on all /mcp requests:

Authorization: Bearer <token>

The /health endpoint is exempt from authentication.

Configuring tokens

Option 1: Environment variable (simple)

# macOS / Linux
MCP_BEARER_TOKENS=sk_abc123,sk_def456 npm start

# Windows PowerShell
$env:MCP_BEARER_TOKENS="sk_abc123,sk_def456"; npm start

Option 2: Token file (rich — with scopes and names)

[
  { "token": "sk_abc123", "name": "ci-pipeline", "scopes": ["read:*", "write:deployments"] },
  { "token": "sk_def456", "name": "readonly-dashboard", "scopes": ["read:*"] }
]

MCP_TOKEN_FILE=./tokens.json npm start

Option 3: Default dev token (zero-config)

When neither MCP_BEARER_TOKENS nor MCP_TOKEN_FILE is set, a single dev token is available:

mcp-dev-token-0123456789abcdef

Disabling authentication

MCP_REQUIRE_AUTH=false npm start

⚠️ Only disable auth for local testing behind trusted networks.

stdio transport

Authentication is not enforced on the stdio transport — it runs as a local subprocess spawned by the MCP client.

Testing

Run the local smoke test to build the server, start it over stdio, and verify the expected tools, resources, resource templates, and prompts:

npm run test:smoke

Testing with the MCP Inspector

The MCP Inspector is the easiest way to explore the server:

# Launches the Inspector and this server (stdio) together
npm run inspect

For the HTTP transport, start the server (npm run start:http) then open the Inspector and connect with:

Transport type: Streamable HTTP
URL: http://127.0.0.1:3000/mcp
Headers: Add Authorization: Bearer mcp-dev-token-0123456789abcdef

HTTP transport details

Method	Path	Purpose
`POST`	`/mcp`	JSON-RPC requests (`initialize` + all subsequent calls). Auth required.
`GET`	`/mcp`	Server-Sent Events stream for server-to-client notifications. Auth required.
`DELETE`	`/mcp`	Terminate a session. Auth required.
`GET`	`/health`	Plain health check (not part of MCP). No auth required.

Sessions are tracked via the Mcp-Session-Id response/request header. The HTTP server binds to 127.0.0.1 by default, and the port defaults to 3000. Both can be overridden:

PORT=3100 npm run start:http                 # macOS / Linux
HOST=0.0.0.0 PORT=3100 npm run start:http    # macOS / Linux, public interface
$env:PORT=3100; npm run start:http           # Windows PowerShell
$env:HOST="0.0.0.0"; npm run start:http      # Windows PowerShell, public interface

Example: raw HTTP handshake with `curl`

curl -i -X POST http://127.0.0.1:3000/mcp \
  -H "Content-Type: application/json" \
  -H "Accept: application/json, text/event-stream" \
  -H "Authorization: Bearer mcp-dev-token-0123456789abcdef" \
  -d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-11-25","capabilities":{},"clientInfo":{"name":"curl","version":"1.0.0"}}}'

The response includes an Mcp-Session-Id header — pass it back as a request header on subsequent calls.

Testing auth failure

Omitting the token or using an invalid one returns:

{
  "jsonrpc": "2.0",
  "error": {
    "code": -32001,
    "message": "Unauthorized: missing Bearer token in Authorization header"
  },
  "id": null
}

Deployment

Docker / Google Cloud Run

docker build -t bearer-mcp-server .
docker run -p 8080:8080 \
  -e MCP_BEARER_TOKENS=your_token_here \
  bearer-mcp-server

Cloud Run sets the PORT environment variable and requires the container to listen on 0.0.0.0:$PORT. The server detects Cloud Run via K_SERVICE and auto-binds appropriately.

Vercel

The api/ directory contains serverless MCP and health handlers. Deploy with the Vercel Git integration or CLI — set the Framework Preset to Other and leave Build Command / Output Directory empty.

Using it with Claude Desktop

Add this to your claude_desktop_config.json (use the absolute path to dist/stdio.js):

{
  "mcpServers": {
    "bearer-mcp-server": {
      "command": "node",
      "args": ["C:\\Users\\Shylendra\\git\\bearer-mcp-server\\dist\\stdio.js"]
    }
  }
}

Restart Claude Desktop, and the server's tools, resources, and prompts will appear.

Project layout

src/
├── server.ts          # createServer() factory + ServerCatalog
├── tools/             # Tool definitions (split by domain)
│   ├── index.ts       # registerTools() aggregator
│   ├── projects.ts    # search_projects, get_project, create_project
│   ├── deployments.ts # deploy_service
│   ├── api-keys.ts    # list_api_keys, rotate_api_key
│   ├── monitoring.ts  # get_metrics, search_logs, run_diagnostic
│   └── echo.ts        # echo tool
├── resources/
│   └── index.ts       # registerResources() — all 6 resources
├── prompts/
│   └── index.ts       # registerPrompts() — all 4 prompts
├── auth/
│   ├── middleware.ts  # Express bearer-token middleware
│   └── tokens.ts      # Token store, validation, loading
├── data/              # Mock data stores
│   ├── projects.ts    # 20 mock projects
│   ├── users.ts       # 5 mock user profiles
│   ├── api-keys.ts    # 8 mock API keys
│   ├── metrics.ts     # Deterministic metrics generator
│   ├── logs.ts        # Deterministic log generator
│   └── system.ts      # System status with incidents
├── stdio.ts           # stdio transport entry point
├── http.ts            # Streamable HTTP transport entry point (with auth)
├── banner.ts          # ANSI startup banner
└── logging.ts         # Structured JSON logging with redaction
api/
├── mcp.ts             # Vercel serverless MCP handler (with auth)
└── health.ts          # Vercel health check
index.ts               # Root HTTP router (node:http)

Environment variables

Variable	Default	Description
`PORT`	`3000`	HTTP listen port
`HOST`	`127.0.0.1`	Listen address (Cloud Run: auto `0.0.0.0`)
`MCP_REQUIRE_AUTH`	`true`	Enforce bearer token auth on HTTP
`MCP_BEARER_TOKENS`	—	Comma-separated valid tokens
`MCP_TOKEN_FILE`	—	Path to JSON file with token definitions
`MCP_CORS_ORIGIN`	`*`	CORS origin for browser access
`MCP_LOG_BODY_LIMIT`	`4000`	Max chars for request/response body logging

Notes

Authentication is enforced on HTTP transport by default. Use MCP_REQUIRE_AUTH=false to disable for local testing.
When using stdio, never write to stdout — it is reserved for the JSON-RPC protocol. Diagnostics go to stderr (console.error).
Authorization headers are redacted in log output.

License

MIT

Available Tools

10 tools

create_projectCreate ProjectA

Create a new project in the platform. Returns the created project with its assigned ID.

ParametersJSON Schema

Name	Required	Description	Default
`name`	Yes	Project name (must be unique)
`tags`	No	Tags for categorization
`region`	No	Deployment region	us-east-1
`language`	Yes	Primary programming language
`description`	No	Project description

TDQS

A4/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It discloses the primary behavior (creation) and that it returns the created project with its assigned ID. However, it does not mention potential side effects, uniqueness constraints, or whether the operation is synchronous, leaving some gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences with zero filler. The key information is front-loaded: what the tool does and what it returns. Every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple create tool with a well-defined schema and clear purpose, the description is sufficiently complete. It covers the outcome and return value. The lack of detailed behavioral caveats is a minor gap, but overall the description provides enough context for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so parameters are fully documented in the schema. The description adds no extra parameter information, which is acceptable per the baseline of 3 when schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'Create a new project in the platform' with a specific verb and resource, clearly distinguishing it from sibling tools like search_projects and get_project which are read operations. The added return value info reinforces purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description makes the usage context explicit: use this when you need to create a new project. It does not explicitly mention alternatives or exclusions, but the clear action plus the nature of sibling tools makes the appropriate use case obvious.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

deploy_serviceDeploy ServiceA

Triggers a deployment for a project to a target environment. Simulates the deployment pipeline and returns a deployment ID for tracking.

ParametersJSON Schema

Name	Required	Description	Default
`branch`	No	Git branch or tag to deploy	main
`message`	No	Deployment notes or reason
`commitSha`	No	Specific commit SHA to deploy (uses branch HEAD if omitted)
`projectId`	Yes	The project ID to deploy
`environment`	No	Target deployment environment	staging

TDQS

A3.7/5.0

Behavior3/5

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 does disclose that the deployment pipeline is simulated and that a deployment ID is returned, which is useful. However, it does not explain side effects, permissions, or what happens after the simulation, leaving gaps in transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, effectively communicating the core action, the simulation nature, and the return value. There is no fluff or repetition, making it highly concise and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

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 explains the return value (deployment ID) but does not detail the response structure, possible errors, or specific simulation behaviors. It is adequate for a simple tool but leaves some contextual gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all five parameters. The description adds no additional meaning to the parameters themselves, such as how the environment or commit SHA interact with the simulation. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool triggers a deployment for a project to a target environment, using specific verbs and resources. It also mentions the simulation aspect, distinguishing it from the sibling tools which are focused on project creation, API keys, metrics, logs, and diagnostics.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage when a deployment needs to be triggered, but it does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or prerequisites. It is not misleading, but the guidance is implicit rather than explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

echoEchoA

Echoes back the text you send. Useful as a connectivity and authentication check.

ParametersJSON Schema

Name	Required	Description	Default
`text`	Yes	The text to echo back

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description takes on full responsibility for behavioral disclosure. It accurately describes that the tool echoes back input and implies no side effects, which is appropriate for a simple test tool. The authentication check context adds transparency about its expected use without contradicting any annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only two sentences, with the primary action in the first sentence and the purpose in the second. Every word contributes value, with no fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool of this low complexity, the description is complete. It explains what it does, when to use it, and the schema fully covers the parameter. No output schema is needed, and the description sufficiently covers all necessary context for a simple echo tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description coverage is 100% for the single parameter, so the schema already fully explains the 'text' parameter. The description adds minimal extra meaning beyond restating that the text is echoed back, meeting the baseline of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function with a specific verb ('Echoes back') and resource ('the text you send'). It also provides an additional purpose ('connectivity and authentication check'), which distinguishes it from the sibling tools that deal with projects, deployments, and API keys.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool (as a connectivity and authentication check), providing clear context. It does not mention exclusions or alternatives, but for a simple echo test tool this is sufficient.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_metricsGet MetricsA

Get usage and performance metrics for a project over the last 24 hours. Returns hourly data points with request counts, errors, and latency percentiles.

ParametersJSON Schema

Name	Required	Description	Default
`projectId`	Yes	The project ID to get metrics for

Output Schema

ParametersJSON Schema

Name	Required	Description
`period`	Yes
`points`	Yes
`summary`	Yes
`projectId`	Yes

TDQS

A4.3/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It transparently states the time range, the granularity (hourly data points), and the data fields returned. It doesn't explicitly mention read-only behavior, but the focus on returning metrics strongly implies it is a safe read operation; no side effects are indicated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences that lead with the action and scope, then describe the return format. Every word adds value, with no redundancy or filler. It is appropriately sized for the tool's simplicity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is simple (one parameter) and an output schema is present. The description covers the purpose, the time window, and the type of data returned, which is complete enough for an agent to select and invoke the tool. It doesn't need to detail return formats since the output schema exists.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already fully describes the sole parameter (projectId) with a clear description. The tool description adds no additional parameter-level detail beyond referencing 'a project', so it doesn't improve on the schema's coverage. The baseline of 3 applies because schema coverage is 100%.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action ('Get usage and performance metrics'), the target resource ('a project'), and a specific time window ('last 24 hours'). It also differentiates from siblings like get_project and search_logs by specifying the metric data (request counts, errors, latency percentiles).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use the tool: to retrieve recent usage and performance metrics for a project. It doesn't explicitly mention alternatives or exclusions, but the specific scope ('last 24 hours') implies when it would be appropriate. Sibling tools like get_project are for different purposes, though this is not stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_projectGet ProjectA

Get full details for a single project by its ID.

ParametersJSON Schema

Name	Required	Description	Default
`projectId`	Yes	The project ID (e.g. 'proj_001')

Output Schema

ParametersJSON Schema

Name	Required	Description
`id`	Yes
`name`	Yes
`tags`	Yes
`owner`	Yes
`region`	Yes
`status`	Yes
`language`	Yes
`createdAt`	Yes
`updatedAt`	Yes
`description`	Yes
`environmentCount`	Yes

TDQS

A4.1/5.0

Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden of indicating behavior. 'Get' clearly implies a read-only operation, but the description does not disclose error handling, authentication requirements, or what happens if the project is not found.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that immediately states the operation and scope without any filler. It is efficiently written and easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With one parameter, an output schema, and a simple read-only retrieval, the description adequately covers the tool's purpose and context. The sibling tools provide sufficient contrast, and the description is complete for this simple tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already fully describes the projectId parameter with an example. The description adds 'by its ID' which reinforces the parameter's purpose but does not introduce new semantic detail beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool retrieves full details for a single project by ID. The verb 'Get' and resource 'project' are specific, and the scope 'single project by its ID' distinguishes it from search_projects.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear usage context: use this tool when you have a project ID and need full details. However, it does not explicitly mention alternatives like search_projects for finding projects without an ID.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

list_api_keysList API KeysA

List all API keys for a project. Keys are returned with masked values — the full key is only shown at creation time.

ParametersJSON Schema

Name	Required	Description	Default
`projectId`	Yes	The project ID to list keys for

TDQS

A3.8/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses a key behavioral trait: keys are masked and full values only appear at creation time. This is valuable beyond the basic 'list' semantics, though it omits any auth/permission context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no fluff, front-loaded with the main action and scope. Every sentence contributes meaningful information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple list tool with one parameter and no output schema, the description explains the key behavioral nuance (masked keys). It could mention what happens with no keys or any return format, but is sufficiently complete for common use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema fully describes the single parameter (projectId) with 100% coverage. The description adds no additional parameter semantics, so the baseline of 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states 'List all API keys for a project' with a specific verb, resource, and scope. This clearly distinguishes it from siblings like rotate_api_key or create_project.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided about when to use this tool versus alternatives. It implies listing keys for a project but gives no exclusions or mentions of related tools like rotate_api_key.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

rotate_api_keyRotate API KeyA

Rotate (regenerate) an existing API key. The old key is immediately invalidated and a new key value is returned. This is the only time the full key is visible.

ParametersJSON Schema

Name	Required	Description	Default
`keyId`	Yes	The API key ID to rotate (e.g. 'key_001')

TDQS

A4.1/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are present, so the description carries the full burden. It discloses critical behavior: immediate invalidation of the old key, return of the new key value, and the fact that this is the only time the full key is visible. This is valuable for a destructive, security-sensitive operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences front-load the core action and include essential behavioral warnings. Every sentence earns its place without unnecessary fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the simple single-parameter tool, the description fully explains the outcome (new key returned), a crucial side effect (old key invalidated), and a security note (only time full key visible). It is complete for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the parameter keyId is already documented. The description adds no extra meaning about the parameter beyond the schema, warranting the baseline score of 3.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Rotate (regenerate) an existing API key') and the resource (API key). It distinguishes from sibling tools like list_api_keys, which only lists keys without rotating them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool (when you need a new key value or the full key), but it does not explicitly mention alternatives such as list_api_keys for viewing key metadata. No exclusions or when-not-to-use guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

run_diagnosticRun DiagnosticA

Run a comprehensive health diagnostic on a project. Checks connectivity, recent errors, configuration validity, and resource utilization. Returns structured results.

ParametersJSON Schema

Name	Required	Description	Default
`projectId`	Yes	The project ID to run diagnostics on

Output Schema

ParametersJSON Schema

Name	Required	Description
`checks`	Yes
`overall`	Yes
`projectId`	Yes
`timestamp`	Yes
`projectName`	Yes

TDQS

A3.6/5.0

Behavior2/5

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 side effects and safety. It states that it returns structured results and lists checks, but it never explicitly says whether this is a read-only, non-destructive operation, or whether any special permissions or rate limits apply. The word 'run' could even imply side effects, creating ambiguity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and front-loaded: the first sentence states the core purpose, and the second adds detail in a structured list-like fashion. Every sentence earns its place with no fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with a single parameter, a clear purpose, and an output schema (which is noted as present), the description is largely complete. It covers what the tool checks and that it returns structured results, leaving the output schema to define return values. The only minor gap is explicit usage guidance, which is already captured under the usage dimension.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema description covers projectId fully ('The project ID to run diagnostics on'). The description adds no additional semantic detail beyond the schema, but the baseline is 3 given the high schema coverage. No parameter information is missing.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Run') and clearly identifies the resource ('a comprehensive health diagnostic on a project'). It lists concrete aspects checked (connectivity, recent errors, configuration validity, resource utilization) and distinguishes itself from sibling tools like get_metrics or search_logs by being a holistic diagnostic rather than a focused metric or log query.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use this tool—when you need an overall health check of a project—but it does not explicitly mention alternatives or exclusions. There is no guidance on when to prefer search_logs or get_metrics instead. It is adequate but lacks explicit usage boundaries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_logsSearch LogsA

Full-text search across application log entries. Filter by project, severity level, or free-text query. Returns the most recent matching entries.

ParametersJSON Schema

Name	Required	Description
`level`	No	Filter by log severity level
`limit`	No	Maximum number of log entries to return
`query`	No	Full-text search term to match in log messages
`projectId`	No	Filter logs to a specific project

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses that this is a read-only search operation (via 'search'), the available filters, and the ordering ('most recent'). It does not mention auth requirements or rate limits, but these are not critical for a search tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with no filler. The action and resource are front-loaded, and every clause adds relevant detail about filters and result ordering.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-parameter tool with no output schema, the description is mostly complete: it explains behavior, filters, and result ordering. It lacks explicit mention of return format or time range constraints, but these are not critical for a straightforward log search.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema documents all parameters. The description adds context by mapping filters to user language (project, severity, free-text) but does not introduce new meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly specifies the verb ('search') and resource ('application log entries'), distinguishing it from sibling tools like search_projects. The resource is explicit and unique among the listed siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description states the tool filters by project, severity level, or free-text query, and returns the most recent matches, giving a clear context for use. However, it does not explicitly name alternatives or state when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

search_projectsSearch ProjectsA

Search for projects by name, language, status, or tags. Returns paginated results with metadata.

ParametersJSON Schema

Name	Required	Description
`page`	No	Page number for pagination
`tags`	No	Filter by tags (projects matching ANY tag are returned)
`limit`	No	Number of results per page
`query`	No	Full-text search across project name and description
`status`	No	Filter by project status
`language`	No	Filter by programming language (e.g. 'typescript', 'python', 'go', 'rust')

Output Schema

ParametersJSON Schema

Name	Required	Description
`page`	Yes
`limit`	Yes
`total`	Yes
`results`	Yes

TDQS

A4.2/5.0

Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the burden of behavioral disclosure. It states that results are paginated and include metadata, which are useful behavioral traits beyond the name. However, it does not detail the metadata contents or any edge-case behavior, so it is not exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that front-loads the purpose and then the behavior (pagination/metadata). No unnecessary words or repetition; every clause adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has six optional parameters and no annotations, but the description covers the core purpose and result behavior, and the output schema exists. It is complete enough for an agent to decide when to invoke the tool and understand pagination. It lacks explicit alternative guidance, but the search context is clear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 100% coverage with descriptions for all six parameters, so the baseline is 3. The description briefly mentions filtering by name, language, status, or tags, which overlaps with schema descriptions but adds no extra semantics. It does not clarify the 'ANY tag' behavior or the full-text query details, relying on the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: searching for projects by specific criteria (name, language, status, tags). It uses a specific verb ('search') and names the resource ('projects'), distinguishing it from siblings like get_project (single project) or search_logs (logs). The listing of filter criteria adds precision.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use the tool (when you need to find projects due to the listed criteria) but does not explicitly mention alternatives or exclusions. It gives clear context for usage without comparing to siblings or stating when not to use it, so it falls short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

TDQS

A3.9/5.0

Disambiguation5/5

Each tool targets a distinct resource and action: projects (create, get, search), deployments, API keys (list, rotate), metrics, logs, diagnostics, and connectivity. There is no overlap or ambiguity between tool purposes.

Naming Consistency4/5

Most tools follow a clear verb_noun snake_case pattern (create_project, search_logs, rotate_api_key). The only deviation is 'echo', which lacks a noun object, but this is a minor utility and does not undermine the overall pattern.

Tool Count5/5

With 10 tools, the server is well-scoped for a platform management API. Each tool covers a distinct aspect of project and deployment management, observability, and diagnostics, without unnecessary bloat.

Completeness3/5

The server covers project creation, retrieval, search, and deployment, but lacks update/delete operations for projects and API key creation/deletion. Deployment status tracking is also missing. These are notable gaps that agents may need to work around.

Resources

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