Skip to main content
Glama
liliangshan

mcp-server-apidebug

by liliangshan

default_api_debug

Execute API requests for debugging with automatic content-type detection. Supports GET, POST, PUT, DELETE, PATCH methods, custom headers, query parameters, and flexible body formats: JSON, form data, XML, plain text.

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"

Input Schema

TableJSON 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, XML, HTML or plain text
contentTypeNoContent-Type for request body (optional, will auto-detect if not specified)
Behavior3/5

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

Discloses auto content-type detection and flexible body support, but lacks warnings about security, potential side effects (e.g., write operations), or return format. With no annotations, the description carries the burden and is adequate but not thorough.

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?

Two concise sentences with front-loaded purpose and illustrative examples. No redundant or vague language.

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?

Lacks explanation of return value, error handling, or behavioral constraints (e.g., read-only vs mutating). Given no output schema and no annotations, the description leaves significant gaps for a debug tool.

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?

Schema coverage is 100% so baseline is 3. The description adds value by showing how parameters combine in real-world examples (e.g., query with GET, body with POST), beyond the schema's individual 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 tool executes API requests with auto-detection and flexible formats. It provides specific examples that illustrate usage with different methods and bodies, distinguishing it from siblings like config or execute.

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?

No guidance on when to use this tool vs alternatives (e.g., default_api_execute). No mention of when not to use or prerequisites.

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/liliangshan/mcp-server-apidebug'

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