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scout-mcp

scout-mcp

by tusharchaudharryy
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

web_search

Read-only

Search the web through a private SearXNG instance to retrieve titles, URLs, snippets, and source engines for a query, with optional time-range and result-count filters.

Instructions

Search the web through a private SearXNG instance.

    Returns title, URL, snippet and the engines that found each result. Snippets are short: call
    fetch_page on a result before relying on it.

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": "web_search"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesSearch terms, e.g. 'red palm weevil acoustic detection'.
time_rangeNoOnly results from the last day/week/month/year.
max_resultsNoHow many results to return.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and openWorldHint, so the safety and reach profile is covered structurally. The description adds value beyond that by naming the exact result fields (title, URL, snippet, engines), warning that snippets are truncated, and prescribing the fetch_page follow-up -- real behavioral context an agent would otherwise have to discover empirically.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the action and the environment, then the return shape, then the caution. Nothing is padded. Minor deduction for the embedded indentation/line-break artifact, which slightly muddies the text without harming comprehension.

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, the description is not obliged to enumerate return values, yet it briefly does so anyway, and the fully documented schema covers all three parameters. The only remaining gap is sibling disambiguation against search_docs, which is the one thing an agent could still get wrong.

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%: query, time_range and max_results each carry their own description and defaults in the schema. The description adds no syntax, formatting or constraint detail beyond that, so it neither compensates nor detracts; baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Search the web") plus a meaningful qualifier: results come through a private SearXNG instance, which tells the agent this is not a general public search API. It does not explicitly contrast itself with the docs-oriented siblings (search_docs, read_doc), so the differentiation is left to the resource noun alone.

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 gives a clear downstream rule -- call fetch_page on a result before relying on it -- which is genuine usage guidance about how to consume results. It stops short of saying when to pick this over search_docs, or when a web search is inappropriate (e.g. internal documentation questions), so selection guidance is only implied.

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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