A
license-
quality-
maintenanceSearch and discover 500+ tools, APIs, and services for AI agents. Browse 15 categories, get recommendations, and access structured metadata including auth methods, free tiers, and example calls.
1
Agent Radar
Server Details
Search, inspect, recommend, and explain rated AI tools through Agent Radar.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- zation/agent-radar
- GitHub Stars
- 1
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
MCP client
Glama
MCP server
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
100% free. Your data is private.
Tool Definition Quality
A4/5.0
Tool DescriptionsA
Average 3.6/5 across 4 of 4 tools scored.
Server CoherenceA
Disambiguation5/5
Each tool targets a distinct operation: explain_rating for detailed rating breakdown, get_tool_card for full card retrieval, recommend_tools for task-based suggestions, and search_tools for querying the database. No overlapping purposes.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (explain_rating, get_tool_card, recommend_tools, search_tools) using snake_case, making the set predictable.
Tool Count5/5
With only 4 tools, the server is tightly scoped to cover core operations (search, retrieve details, explain ratings, recommend) without excess or deficiency.
Completeness5/5
The tool set covers the primary needs of a tool registry: searching, retrieving individual cards, explaining ratings, and getting recommendations. There are no obvious gaps given the stated purpose.
Available Tools
4 toolsexplain_ratingExplain a tool ratingARead-onlyIdempotentInspect
Return rating dimensions, explanations, penalties, and boosts for one tool_id.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tool_id | Yes | Stable Agent Radar tool identifier, usually obtained from search_tools results. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
A3.6/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds no additional behavioral context such as side effects, error handling, or data freshness. It merely restates the purpose.
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, clear sentence with no filler. Every word contributes to understanding the tool's function.
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?
Given the simple tool (1 required param, output schema exists), the description covers the return content (dimensions, explanations, penalties, boosts). It is complete enough for an agent to decide to invoke it, though it could mention what happens if tool_id is invalid.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage and only one parameter, the description adds value by specifying the origin of tool_id ('usually obtained from search_tools results'), which aids agent understanding. Baseline 3 is exceeded.
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 verb 'Return' and the specific resource: 'rating dimensions, explanations, penalties, and boosts for one tool_id.' It distinguishes itself from siblings like get_tool_card (which likely returns a tool card) and search_tools (which searches for tools).
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?
The description does not provide explicit guidance on when to use this tool versus alternatives. It only implies usage when needing rating details for a single tool, but lacks exclusions or comparisons to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_tool_cardGet an Agent Radar tool cardARead-onlyIdempotentInspect
Return one Tool Card and its Rating Result by stable tool_id.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| tool_id | Yes | Stable Agent Radar tool identifier, usually obtained from search_tools results. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
A3.6/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds that it returns one Tool Card and Rating Result, but does not disclose any behavioral traits beyond what annotations imply. Since annotations carry the burden, the description adds minimal value.
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?
Single sentence that is front-loaded with the action and resource. No wasted words; every part 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?
Given the existence of an output schema, clear annotations, and full schema coverage for the single parameter, the description is sufficient for a simple retrieval tool. It lacks mention of error conditions or rate limits, but these are not critical for such a 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?
Schema description coverage is 100% and the only parameter (tool_id) is well-described in the schema. The description's mention of 'stable tool_id' reinforces the schema but does not add new meaning. Baseline of 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?
Description clearly states the verb 'Return', resource 'Tool Card and its Rating Result', and specifies the key identifier 'by stable tool_id'. It distinguishes from siblings like search_tools (search), recommend_tools (recommendation), and explain_rating (explanation) by focusing on fetching a single card by ID.
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 mentions 'usually obtained from search_tools results', implying a usage flow from search to card retrieval. However, it does not explicitly state when not to use this tool or compare it to sibling tools like recommend_tools or explain_rating. The guidance is implied but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
recommend_toolsRecommend toolsBRead-onlyInspect
Recommend known tools for a task using request-scoped LLM credentials when required.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| task | Yes | Natural-language development task for which Agent Radar should recommend suitable AI tools. | |
| model | No | LLM provider model identifier recognized by Agent Radar. Omit it to use the server-configured or registry default model. | |
| top_k | No | Maximum number of recommended candidates to return, from 1 to 50. Defaults to 5 when omitted. | |
| budget | No | Natural-language cost constraint, such as free, free_or_low_cost, or a project-specific budget. | |
| environment | No | Execution contexts such as local development, CI, browser, cloud, IDE, or production. | |
| output_format | No | Preferred presentation format for recommendation content: json or markdown. MCP still returns structured content. | |
| existing_tools | No | Tools already available to the project or agent, used as compatibility and duplication context. | |
| risk_tolerance | No | Maximum preferred risk tolerance for the recommendation: low, medium, or high. | |
| language_or_stack | No | Programming languages, frameworks, runtimes, or other stack constraints relevant to the task. | |
| allowed_permissions | No | Permission scope names the caller is willing to allow; candidates outside these boundaries are treated conservatively. | |
| preferred_tool_types | No | Agent Radar tool types to prefer when selecting candidates. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
B3.4/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, indicating a safe read operation. The description adds that it uses 'request-scoped LLM credentials when required,' which is useful but lacks detail on credential handling or side effects. It does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it concise. It front-loads the core action ('Recommend known tools for a task') but adds a somewhat redundant clause about credentials. Could be slightly tighter, but overall efficient.
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 11 parameters, a rich schema, and an output schema, the description is minimal. It does not explain what 'known tools' means or provide context for the recommendation task. The output schema covers return values, so completeness is adequate but not thorough.
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 coverage is 100%, with all 11 parameters described in detail. The description does not add additional meaning beyond the schema. Baseline of 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's purpose: to recommend known tools for a task. It uses a specific verb ('Recommend') and resource ('tools'), and the action is distinct from its siblings (explain_rating, get_tool_card, search_tools).
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?
The description provides no guidance on when to use this tool versus alternatives like search_tools or get_tool_card. The mention of 'request-scoped LLM credentials' hints at a specific context but does not compare or contrast with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_toolsSearch Agent Radar toolsARead-onlyIdempotentInspect
Search Agent Radar Tool Cards by query text and optional type, tag, or risk filters.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| query | No | Free-text tool name, capability, or task to search for. Use an empty string to browse the highest-rated matching catalog entries. | |
| top_k | No | Maximum number of results to return, from 1 to 50. Defaults to 5. | |
| filters | No | Optional exact-match filters applied before search ranking. |
Output Schema
ParametersJSON Schema
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Tool Definition Quality
A3.8/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description does not contradict these but adds minimal behavioral context beyond stating the search operation. It could mention ranking or return behavior.
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?
A single sentence of 12 words that is front-loaded with the core action and resource. Every word is necessary, and the structure is clean and efficient.
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?
Given the tool's moderate complexity (3 parameters, nested object, output schema exists), the description is largely complete. It covers the main filtering options. A hint about semantic search or ranking would improve completeness, but not essential.
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 parameters. The description only paraphrases the parameters without adding new meaning. Baseline score of 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 verb 'Search', the resource 'Agent Radar Tool Cards', and the parameters 'by query text and optional type, tag, or risk filters'. It effectively differentiates from sibling tools like explain_rating, get_tool_card, and recommend_tools.
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 for searching with filters but does not explicitly state when to use this tool versus alternatives like recommend_tools or get_tool_card. No when-not-to-use or contextual guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
No comments yet. Be the first to start the discussion!
Related MCP Servers
- AlicenseAqualityCmaintenanceEnables AI agents to search, score, review, and submit tools from the SkillsIndex directory of 11,000+ AI agent tools.926MIT
- AlicenseAqualityBmaintenanceEnables AI agents to search, browse, and recommend tools from the Hermes Agent ecosystem directory with zero configuration.89MIT
- AlicenseAqualityDmaintenanceGive your AI agent access to 8,400+ software tools — search, compare, get pricing, find alternatives, and discover the best tool for any use case.6122MIT