Skip to main content
Glama
zhangwanli09

internal-swagger-mcp

by zhangwanli09

Get Swagger API Detail

swagger_get_api_detail
Read-onlyIdempotent

Retrieve full API documentation for a single endpoint, including parameter definitions, response examples, and mock data by specifying service, method, and path.

Instructions

Get full details of a single API interface, including all parameter definitions and response examples.

Parameters:

  • source (required): Service name, from the [service name] returned by swagger_list_sources or swagger_search_api.

  • method (required): HTTP method, e.g. "GET", "POST".

  • path (required): Full interface path, e.g. "/qmAuthorityCenter/systemFun/initPerformanceSolution".

Response includes:

  • Basic interface info (name, description, status, Content-Type).

  • Full definitions for Query / Path / Header / Form / Body parameters (name, type, required, description). Required column: "是" = required, "否" = optional, "?" = platform metadata is ambiguous (checkType=1 with no error message — cross-check with backend code or treat as optional).

  • Sub-fields of nested Object parameters.

  • Response results (Demo JSON + output field table).

  • Mock response field table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesFull interface path, e.g. /qmAuthorityCenter/systemFun/initPerformanceSolution
methodYesHTTP method.
sourceYesService name, from swagger_list_sources or swagger_search_api results.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
pathYes
methodYes
statusYes
responsesYes
mockFieldsYes
moduleNameYes
parametersYes
sourceNameYes
contentTypeNo
descriptionYes
bodyRequestDemoNo
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds meaningful behavioral details: what the response includes (basic info, parameter definitions, response examples, mock field table) and explains the 'Required' column semantics ('是' = required, '否' = optional, '?' = ambiguous). This goes beyond annotations without contradicting them.

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 well-structured with a clear first sentence and bullet points for parameters and response sections. While it is longer than necessary, every bullet adds meaningful detail (e.g., required column semantics, response components). It is front-loaded with the primary purpose and avoids 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?

Given the output schema exists (so return values are formally specified) and annotations declare safety traits, the description covers the essential operational context: how to specify the target API (source, method, path) and what the response contains. It does not cover error scenarios or rate limits, but these are not critical for a read-only detail operation. The description is sufficiently complete for a well-annotated 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 input schema has 100% description coverage for all three parameters, with clear explanations (e.g., method enum, path example, source from sibling tools). The description adds little beyond what the schema already provides—the source field is explained more explicitly in the schema, and the path/method examples are duplicated. Baseline 3 is appropriate 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 clearly states 'Get full details of a single API interface, including all parameter definitions and response examples.' This is a specific verb+resource combination that distinguishes it from sibling tools like swagger_list_sources (listing sources) and swagger_search_api (searching APIs).

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 tells the agent that the 'source' parameter comes from the output of swagger_list_sources or swagger_search_api, providing context on when to use this tool. However, it does not explicitly state when not to use it or compare with alternatives, so it falls short of a perfect 5.

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

Install Server

Other Tools

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/zhangwanli09/internal-swagger-mcp'

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