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scout-mcp

scout-mcp

by tusharchaudharryy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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search_docs

Read-only

Search your own .md and .txt notes with keyword-based BM25 to find matching passages and return document names, section headings, and relevance scores.

Instructions

Keyword search (BM25) over the user's own notes (.md and .txt files in the docs folder).

    Returns passages with the document name, section heading and score. Use read_doc for the
    whole document.

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
queryYesKeywords to look for in the user's notes.
top_kNoHow many passages to return.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description still adds real value by naming BM25, which warns the agent this is lexical matching without synonym or semantic recall, and by describing the result shape (passage, document name, section heading, score).

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 short sentences, front-loaded with the mechanism and scope, then the disambiguation pointer. Nothing is padded and no sentence restates the tool name.

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?

With an output schema present, return values need no explanation, and annotations carry the safety profile; what remains (file types, scope, fallback) is covered. A minor gap is that it does not mention what happens on zero hits or that results are capped at top_k's maximum of 20.

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 both query and top_k are already documented. The description reinforces that query is keyword-based and that results come back as passages, which gives top_k a unit, but adds no syntax, format, or range detail beyond the schema. Baseline 3 applies.

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?

States a specific verb and mechanism (keyword search, BM25) over a specific resource (the user's own .md/.txt notes in the docs folder). The scope 'user's own notes' implicitly separates it from web_search, and read_doc is named as the alternative for whole documents.

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 line 'Use read_doc for the whole document' gives a concrete alternative and implies the selection rule: search this tool, then read the full doc. It stops short of stating explicit when-not-to-use conditions (e.g. conceptual/semantic queries where BM25 will miss paraphrases).

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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