MCP OpenAPI Discovery

Server Quality Checklist

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Latest release: v0.5.0
Disambiguation4/5
Most tools have clearly distinct purposes, though search_endpoints and list_endpoints could be confused due to both listing endpoints; however, their descriptions differentiate search vs. filtering.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern (e.g., call_endpoint, detect_openapi), making them predictable and easy to distinguish.
Tool Count5/5
8 tools is well within the optimal range (3-15) and covers the core workflow of OpenAPI discovery and interaction without being excessive.
Completeness5/5
The tool set fully covers the lifecycle: detect, list, get details, call, and includes advanced features like semantic search, relationship discovery, sequencing, and parameter tracing.
Average 3.3/5 across 8 of 8 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit in the last 12 weeks
- Last stable release on May 14, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
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  ]
}
```
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral traits. It only states the purpose and does not disclose whether the tool is read-only, requires authentication, or any other behavioral characteristics.
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 action and output. It is concise, front-loaded, and contains no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity (4 parameters including a nested auth object) and no output schema, the description is insufficient. It does not explain what 'details' includes, how authentication for protected docs works, or the required combination of parameters.
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% description coverage, so the schema itself documents parameters. The tool description does not add additional meaning beyond what is already in the schema, resulting in a baseline score of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns request/response details for a specific endpoint. However, it does not differentiate from sibling tools like find_related_endpoints or trace_parameter_usage, which could be more specific about endpoint details.
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 such as list_endpoints or search_endpoints. No usage context or conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
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 describes the input and criteria, but omits any indication of side effects (none expected), performance, or whether it's a read-only operation. The agent lacks insight into the tool's safety or cost.
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, front-loaded sentence that efficiently conveys the core purpose. No wasted words. However, it could be slightly more structured by separating criteria, but overall it's concise and clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description should explain the return value (e.g., list of endpoints, their structure). It does not. The tool has five parameters including a nested auth object, and the description only briefly mentions the criteria. The agent lacks information about output format and missing details like whether the source endpoint is included.
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 each parameter has a description. The description adds context about the algorithm (e.g., 'parent/child URL patterns'), but does not significantly enhance parameter understanding 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 function: finding structurally related endpoints based on specific criteria like shared resource paths, identifiers, tags, and URL patterns. This distinguishes it from sibling tools like search_endpoints (keyword search) and get_endpoint_details (specific endpoint info).
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. It does not specify prerequisites, when not to use it, or compare with sibling tools like search_endpoints or list_endpoints. The agent must infer usage from the criteria mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description alone must define behavior. It discloses that the tool traces across specified locations, but omits critical details such as whether it makes network requests, requires authentication, has rate limits, or can be slow. The behavior is only partially transparent.
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 that efficiently conveys the tool's core function without verbosity. Every word adds value, and the structure is front-loaded with the key action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite high schema coverage, the tool has 9 parameters including nested objects and no output schema. The description is too brief given this complexity; it lacks details on output format, side effects, error handling, and performance implications, making it incomplete for an agent to use confidently.
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%, so the schema already describes all 9 parameters thoroughly. The description does not add additional meaning beyond the schema, 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 purpose: tracing where a parameter or field is used across various API spec locations (path, query, request/response bodies). It uses a specific verb ('trace') and resource ('parameter or field'), and distinguishes from sibling tools that focus on endpoints or calls.
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 any guidance on when to use this tool vs. alternatives. There is no mention of prerequisites, context, or exclusions, leaving the agent without decision support for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions optional auth but fails to disclose error handling, idempotency, or mutual exclusivity of body and rawBody. The description is too brief for a tool with 11 parameters.
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 of 25 words, which is concise and front-loaded. However, it could benefit from a brief second sentence about auth usage or parameter relationships.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the complex input schema with 11 parameters, nested objects, and no output schema, the description is minimal. It doesn't explain that the url can be a docs page, that body and rawBody are alternatives, or that path params are required. The description is incomplete 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?
All parameters have schema descriptions covering 100%, so the baseline is 3. The description adds value by mentioning automatic auth, but overall it does not significantly enhance the schema's clarity.
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: calling an endpoint from an OpenAPI document. It includes key features like automatic auth and data sending. It distinguishes from sibling tools that deal with detection and listing, not actual calling.
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?
Usage is implied: you call an endpoint after discovery. No explicit when-to-use or when-not-to-use. No alternatives are mentioned. The description assumes the agent knows this is the main execution tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It does not mention whether the tool fetches the document, how detection works, what happens with invalid URLs, or any side effects. The description adds little beyond 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 sentence that is front-loaded with the core purpose. It is concise and contains no unnecessary words or information.
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 2 parameters and no output schema, the description is adequate but minimal. It does not describe return values, error behavior, or edge cases, but it conveys the essential function. It is complete enough for a simple tool but could be improved.
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%, with clear descriptions for 'url' and 'auth' parameters. The tool description does not add additional semantic context beyond what the schema already provides, so a 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 tool's purpose: detect an OpenAPI/Swagger document from a URL and summarize the API structure. It uses a specific verb (detect) and resource (OpenAPI document), and distinguishes from siblings like call_endpoint or list_endpoints.
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, no when-not-to-use conditions, and no mention of prerequisites or limitations. It only describes what the tool does.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It mentions 'server-side semantic-style scorer' but does not specify whether the search is destructive, any authentication requirements, rate limits, or side effects. The description is insufficient 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is relatively compact and front-loaded with the key action. However, it could be broken into multiple sentences for better readability without losing precision.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 6 parameters, 2 required, and no output schema. The description does not explain the return format, sorting, pagination, or how the scoring works. It is incomplete for an AI agent to fully understand expected behavior.
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?
Input schema has 100% description coverage for all 6 parameters, so the baseline is 3. The description adds no additional meaning beyond what the schema already provides; it does not explain parameter semantics or constraints.
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 'cached endpoints', and the context 'previously detected OpenAPI spec' with a specific method 'semantic-style scorer over endpoint metadata and schema field names'. It distinguishes itself from siblings like list_endpoints (listing all) and find_related_endpoints (related endpoints).
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 within a previously detected spec but does not explicitly state when to use this over alternatives or when not to use it. No exclusion criteria or alternative tool references are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description bears full burden. It mentions 'likely' sequence, implying non-determinism, but lacks details on side effects, required permissions, or how the suggestion is generated. Adequate but minimal.
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?
Single sentence, no redundant phrasing. Front-loaded with key action and resource. Very concise, though could benefit from slight expansion for clarity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and six parameters, the description is too brief. It does not explain the return format, how dependencies are explored, or limitations. For a tool that plans call sequences, more context is needed.
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 description adds no extra parameter meaning beyond listing an example usage scenario. 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?
Description clearly states verb 'suggest' and resource 'API call sequence' for reaching a target endpoint or accomplishing a goal. It distinguishes from sibling tools like call_endpoint by focusing on planning rather than execution.
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?
Provides an example of when to use (e.g., creating prerequisites), but does not explicitly state when not to use or mention alternatives like call_endpoint for single requests. Usage is implied but not fully guided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description implies a read-only operation (listing), which is accurate. However, since no annotations are provided, the description carries the full burden. It could explicitly state that the tool does not modify any resources or require special authentication beyond what is already specified in the auth parameter.
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?
Single sentence that front-loads the main action and optional filters. No wasted words, but could benefit from a brief note on default behavior (e.g., includeDeprecated defaults to true).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the absence of an output schema, the description should hint at what the response contains (e.g., list of endpoint objects). It also omits details about pagination (limit parameter) and the fact that includeDeprecated defaults to true. For a tool with 7 parameters and complex nested objects (auth), this is insufficient.
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%, so the baseline is 3. The description adds no new parameter meaning beyond stating that there is optional filtering by tag, method, or path fragment, which is already evident from the schema parameter descriptions.
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 (List endpoints), the resource (discovered OpenAPI document), and the optional filtering capabilities (tag, method, path fragment). It distinguishes itself from sibling tools like call_endpoint, which actually invokes endpoints.
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 the tool is for listing/browsing endpoints, but does not explicitly state when to use this versus other listing tools like search_endpoints or find_related_endpoints. No exclusions or context about prerequisites (e.g., requiring a prior detect_openapi call).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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