docs-rag-mcp

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search_docs

Retrieve relevant documentation chunks from local markdown files using TF-IDF search. Enter a natural-language query to find matching content.

Instructions

Search the documentation corpus with TF-IDF retrieval.

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_docs"
  }
}

Input Schema

Name	Required	Description	Default
`k`	No	Maximum number of chunks to return (default 5).
`query`	Yes	Natural-language search query.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Aug 1, 2026

TDQS

A3.8/5.0

Behavior3/5

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

The description mentions 'TF-IDF retrieval,' which discloses the algorithmic approach, but provides no insight into return behavior, sorting, or side effects. With no annotations, the description carries the burden, yet it lacks detail on what happens when invoking the 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 a single, front-loaded sentence that conveys the core functionality without unnecessary words. Every word earns its place.

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 simple 2-parameter tool and the existence of an output schema, the description adequately covers the purpose. The schema handles parameter details, and the description completes the context. A full 5 would require more detail on expected output or limits, which is already present in schema.

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?

Since the schema covers 100% of parameters with descriptions, the description does not need to add parameter information. It adds no extra semantic value beyond the schema, so baseline 3 is appropriate.

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 'Search the documentation corpus' with a specific verb and resource, and also specifies the retrieval method (TF-IDF). This clearly distinguishes the tool's purpose even without sibling tools.

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 for searching documentation, but does not provide explicit guidance on when to use this tool versus alternatives or any prerequisites. No sibling tools are listed, so it relies on the verb 'Search' to convey its intended use.

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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