Skip to main content
Glama
abeixiaolu

YApi MCP Server

by abeixiaolu
OverviewSchemaRelated ServersScoreDiscussions
TypeScript
Remote

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one retrieves interface details by ID, while the other retrieves them by URL. There is no overlap or ambiguity between their functions, making it easy for an agent to select the correct tool based on the available input.

    Naming Consistency5/5

    Both tools follow a consistent naming pattern: 'yapi-get-interface' with a suffix indicating the input type ('-by-url'). This verb_noun structure is uniform and predictable, enhancing readability and usability across the tool set.

    Tool Count2/5

    With only 2 tools, the server feels under-scoped for a YApi (API management) domain. This minimal set lacks essential operations like creating, updating, or listing interfaces, which are typical for such systems, making it insufficient for comprehensive agent workflows.

    Completeness2/5

    The tool surface is severely incomplete for API management. It only provides retrieval methods (by ID and URL), missing critical CRUD operations such as create, update, delete, or list interfaces. This creates significant gaps that will likely cause agent failures in handling full lifecycle tasks.

  • Average 3.1/5 across 2 of 2 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.

  • Add a glama.json file to provide metadata about your server.

  • 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.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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 states what the tool does (get interface details from a URL) but doesn't describe behavioral traits like error handling, authentication requirements, rate limits, or what '接口详情' (interface details) includes in the response. For a tool with no annotations, this leaves significant gaps in understanding its 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?

    The description is extremely concise and front-loaded: a single sentence stating the purpose followed by a concrete example. Every word earns its place with no redundancy or unnecessary elaboration, making it efficient and easy to parse.

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

    Completeness2/5

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

    Given the tool has no annotations and no output schema, the description is incomplete. It explains what the tool does but lacks crucial context: what '接口详情' (interface details) returns, error conditions, or how it differs from the sibling tool. For a tool with minimal structured data, the description should provide more operational 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?

    The schema description coverage is 100%, with the parameter 'url' fully documented in the schema. The description adds an example URL format ('http://localhost:40001/project/11/interface/api/23'), which provides context but doesn't add significant semantic meaning beyond what the schema already specifies. This meets the baseline score of 3 for high schema coverage.

    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YApi URL获取接口详情' (Get interface details based on YApi URL). It specifies the verb '获取' (get) and resource '接口详情' (interface details), but doesn't distinguish from the sibling tool 'yapi-get-interface' which likely has a different parameter approach. The description provides a concrete example of the URL format, making the purpose specific and actionable.

    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 mentions the sibling tool 'yapi-get-interface' in the context signals, but the description itself doesn't explain the difference (e.g., this tool uses a URL parameter while the sibling might use ID-based parameters). There are no usage prerequisites, exclusions, or comparisons stated.

    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 provided, the description carries full burden for behavioral disclosure. While '获取' (get) implies a read operation, the description doesn't specify authentication requirements, rate limits, error conditions, response format, or whether this is a safe/idempotent operation. It provides minimal behavioral context beyond the basic action.

    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, efficient Chinese sentence that communicates the core functionality without any wasted words. It's appropriately sized for a simple lookup tool with one parameter and gets straight to the point.

    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?

    For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what '接口详情' (interface details) includes in the response, doesn't mention error handling for invalid IDs, and provides minimal behavioral context. Given the lack of structured metadata, the description should do more to compensate.

    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 the single parameter 'interfaceId' documented as '接口ID' (interface ID). The description adds no additional parameter semantics beyond what's already in the schema. The baseline score of 3 is appropriate when the schema provides complete parameter documentation.

    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 action ('获取' - get/retrieve) and resource ('接口详情' - interface details) with the specific condition '根据接口ID' (based on interface ID). It distinguishes from the sibling tool 'yapi-get-interface-by-url' by specifying ID-based lookup rather than URL-based lookup. However, it doesn't explicitly name the sibling alternative.

    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 context through '根据接口ID' (based on interface ID), suggesting this tool should be used when you have an interface ID rather than a URL. However, it doesn't explicitly state when to use this vs. the sibling 'yapi-get-interface-by-url' or provide any exclusion criteria or prerequisites.

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

GitHub Badge

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.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

yapi-mcp MCP server

Copy to your README.md:

Score Badge

yapi-mcp MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/abeixiaolu/yapi-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server