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izjing

mcp-swagger-schema

by izjing
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.1.0

  • Disambiguation5/5

    With only one tool, there is no possibility of ambiguity or overlap between tools. The tool has a clear, singular purpose of retrieving API schemas based on interface paths.

    Naming Consistency5/5

    The single tool name 'get_api_schema' follows a clear verb_noun pattern (get + api_schema). Since there is only one tool, consistency is inherently perfect with no deviations to assess.

    Tool Count2/5

    A single tool is too few for a server named 'mcp-swagger-schema', which suggests a broader scope related to Swagger/OpenAPI schemas. One tool feels thin and limits functionality, such as lacking operations for listing, updating, or validating schemas.

    Completeness2/5

    The tool surface is severely incomplete for the implied domain of Swagger/OpenAPI schema management. While 'get_api_schema' provides retrieval, there are obvious gaps like creating, updating, deleting, or listing schemas, which are essential for full coverage.

  • Average 2.9/5 across 1 of 1 tools scored.

    See the Tool Scores section below for per-tool breakdowns.

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • 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.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

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  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}

    Then . Browse examples.

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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?

    No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions fetching schemas but lacks details on error handling, authentication needs, rate limits, or output format. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves in practice.

    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, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized for a simple tool, though it could be slightly more structured by front-loading key information more explicitly.

    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 lack of annotations and output schema, the description is incomplete. It does not explain what the tool returns (e.g., schema format, error responses) or behavioral aspects like permissions or limitations. For a tool with no structured support, the description should provide more context to be fully helpful.

    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 both parameters in the input schema. The description adds no additional meaning beyond what the schema provides, such as examples or edge cases. With high schema coverage, the baseline score of 3 is appropriate, as the schema does the heavy lifting.

    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's purpose: '根据接口路径获取 Swagger/OpenAPI 的请求和响应 schema' (Get Swagger/OpenAPI request and response schema based on API path). It specifies the verb '获取' (get) and the resource 'schema', making the purpose understandable. However, with no sibling tools mentioned, there's no opportunity to distinguish from alternatives, preventing a perfect score.

    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, prerequisites, or constraints. It simply states what the tool does without context about its application or limitations, such as when it's appropriate to fetch schemas or what happens if the path is invalid.

    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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Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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