rest_api_mcp

search_endpoints

Find REST API endpoints by keyword search across paths, methods, summaries, and descriptions when you don't know the exact endpoint.

Instructions

Fuzzy-search the API spec by keyword. Use this when you don't know the exact path. Searches across path, HTTP method, summary, description, tags, and operationId. Returns matching endpoints with their method, full path, summary, and required parameters.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "search_endpoints"
  }
}

Input Schema

Name	Required	Description	Default
`query`	Yes	Keywords to search for, e.g. 'packs search' or 'inspector shipments' or 'verify otp'
`limit`	No	Max results to return (default 10)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.3.1Apr 16, 2026

TDQS

A4.2/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes the search behavior ('fuzzy-search'), scope ('searches across path, HTTP method...'), and return format ('Returns matching endpoints with their method, full path...'). However, it doesn't mention performance characteristics, rate limits, authentication needs, or error handling, which are gaps for a search tool.

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 perfectly concise and well-structured in two sentences. The first sentence states the purpose and usage guidance, while the second explains search scope and return format. Every word earns its place with zero waste or redundancy.

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 tool's moderate complexity (search functionality with 2 parameters), no annotations, and no output schema, the description does a good job covering purpose, usage, behavior, and returns. However, it lacks details on output structure (beyond listing fields) and error cases, leaving some gaps for the agent to infer.

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%, so the schema already fully documents both parameters. The description doesn't add any parameter-specific information beyond what's in the schema (e.g., it doesn't explain search algorithm details or result ordering). This meets the baseline of 3 when the 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 the tool's purpose with a specific verb ('fuzzy-search') and resource ('API spec'), and distinguishes it from siblings by explaining it's for when you don't know the exact path. It explicitly mentions what gets searched (path, HTTP method, summary, etc.) and what's returned (matching endpoints with method, path, summary, parameters).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: 'Use this when you don't know the exact path.' This clearly indicates when to choose this tool over alternatives like fetch_spec (which presumably fetches the full spec) or request (which makes actual API calls). The context is well-defined with no ambiguity.

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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