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mcp-doc-search

mcp-doc-search

by anujmv
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

Search documents

search_docs

Search local documents to retrieve relevant sources and snippets for grounding AI responses in verified information.

Instructions

Search the local document set for a query and return the most relevant documents with snippets. Use this to ground answers in real sources before responding.

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

NameRequiredDescriptionDefault
queryYesNatural language query or keywords
limitNoMax results

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
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 states the tool returns 'snippets' but does not elaborate on ordering, pagination, authentication, or scope constraints beyond 'local document set'. This is adequate but not fully transparent.

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 two sentences with no extraneous words. The first sentence states the core function, and the second provides usage guidance. It is front-loaded and efficient.

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 simplicity (2 parameters, no output schema, one sibling), the description covers the main purpose and usage context. However, it lacks explicit details about the output structure (e.g., format of snippets), which would be beneficial since no output schema is provided.

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 coverage is 100%, so the schema already documents both parameters. The description does not add any semantic detail beyond what the schema provides, such as clarifying the nature of snippets or the meaning of the limit parameter. Thus, 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 specifies the verb 'search' and resource 'local document set', and distinguishes from the sibling tool 'get_document' by implying it is for retrieval of specific documents, while search_docs is for searching and returning snippets.

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 says 'Use this to ground answers in real sources before responding', providing clear context for when to use the tool. However, it does not explicitly state when not to use it or mention alternatives like get_document.

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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