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MCP Project Standards Server

MCP Project Standards Server

by liliangshan
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api_debug

Execute API requests for debugging with automatic content-type detection and support for JSON, form data, XML, and plain text bodies.

Instructions

API debugging tool for directly executing API requests with automatic content-type detection and flexible body format support. Examples: GET /api/users with query params, POST /api/login with JSON body {"username":"admin","password":"123456"}, PUT /api/users/123 with form data "name=John&email=john@example.com"

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "description": "Simple GET request",
      "url": "/api/users",
      "method": "GET",
      "query": {
        "page": 1,
        "limit": 10
      }
    },
    "name": "api_debug"
  }
}

Input Schema

NameRequiredDescriptionDefault
urlNoAPI URL to execute (required)
methodNoHTTP method (optional, defaults to GET)
headersNoAdditional headers for the request (optional)
queryNoQuery parameters (optional)
bodyNoRequest body (optional) - Supports multiple formats: JSON object, form data, or plain text
contentTypeNoContent-Type for request body (optional, will auto-detect if not specified)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv5.1.0

TDQS

B3.4/5.0
Behavior2/5

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

With no annotations, the description must fully disclose behavior but only mentions automatic content-type detection and flexible body formats. It omits critical details such as error handling, authentication requirements, rate limits, or the potential impact of executing arbitrary requests, leaving significant ambiguity.

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 concise (two sentences plus inline examples) and front-loaded with the core purpose. However, the inline examples make it slightly longer than necessary; still, it efficiently communicates key 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's complexity (6 parameters, no annotations, no output schema), the description covers the basic purpose and provides examples but lacks safety warnings, usage guidelines, and behavioral details. It is adequate but not comprehensive.

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?

The schema already provides 100% coverage with descriptions and examples. The description adds value by emphasizing automatic content-type detection and flexible body format support, and by listing explicit examples that illustrate usage patterns beyond the schema.

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 explicitly states 'API debugging tool for directly executing API requests' with specific features like automatic content-type detection. It clearly identifies the tool's purpose and distinguishes it from siblings through the mention of flexible body format support and automatic detection, even without explicit sibling differentiation.

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 (e.g., api_execute). It does not specify prerequisites, limitations, or when not to use it, leaving the agent without clear decision criteria.

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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