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sweetcornna

free-search-mcp

by sweetcornna
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Python
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Compare URLs side-by-side

compare
Read-onlyIdempotent

Fetch 2-5 URLs and a comparison question, then receive per-URL excerpts for side-by-side analysis and fact triangulation.

Instructions

Fetch 2-5 URLs concurrently and return per-URL excerpts so the LLM can compare them against a single question in one round trip.

Best for:
- Side-by-side product/feature/article comparisons.
- "Compare X to Y" or "How does A differ from B" queries.
- Triangulating a fact across multiple sources.

Not recommended for:
- >5 URLs -> use `fetch_batch`.
- 1 URL -> use `fetch`.
- Don't have URLs yet -> use `search` or `research` first.

Returns:
- markdown (default): a comparison brief with per-URL sections, each
  containing title, sitename, published date, and a smart-truncated excerpt.
- json: {question, urls, excerpts:[{url, title, excerpt, ...}],
  tokens_estimated}.

Common mistakes:
- Asking `compare` to actually answer the question: it returns material,
  the LLM does the comparison.
- Passing >5 URLs and expecting them all to fit in context: use
  `fetch_batch` for bulk reads.

Args:
    question: The comparison question the LLM will answer using the
        returned excerpts.
    urls: 2-5 absolute http(s) URLs.
    format: "markdown" (default) or "json".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlsYes
formatNomarkdown
questionYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.12.0
    • changedOutput schema / (root)
      Previous value: -{
-  "properties": {
-    "result": {
-      "anyOf": [
-        {
-          "type": "string"
-        },
-        {
-          "additionalProperties": true,
-          "type": "object"
-        }
-      ],
-      "title": "Result"
-    }
-  },
-  "required": [
-    "result"
-  ],
-  "title": "compareOutput",
-  "type": "object"
-}New value: +null
  2. Addedv0.2.0

TDQS

A5/5.0
Behavior5/5

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

Beyond the readOnlyHint and idempotentHint annotations, the description discloses concurrency, smart truncation, return format specifics (markdown/json with tokens_estimated), and common mistakes (e.g., asking it to answer the question). No contradiction with annotations; it adds valuable behavioral context.

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 well-structured with sections (intro, best for, not recommended, returns, mistakes, args). It front-loads the core purpose and each sentence earns its place, providing high information density without fluff.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description is fully self-contained: it covers when to use, when not to use, parameter details, return formats, and common pitfalls. No output schema exists, but the return description is detailed enough for an agent to handle responses correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. The 'Args' section explains every parameter: question (purpose), urls (count and format), format (enum with default). This is complete and adds meaning beyond the bare schema.

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 states a specific action ('Fetch 2-5 URLs concurrently and return per-URL excerpts'), identifies the resource (URLs), and clarifies the outcome (enables comparison). It also distinguishes itself from siblings by naming fetch_batch and fetch as alternatives for different URL counts, leaving no ambiguity.

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?

Explicit 'Best for' and 'Not recommended for' sections give concrete usage conditions: >5 URLs → fetch_batch, 1 URL → fetch, no URLs → search/research. This is direct, actionable guidance on when to use this tool versus alternatives.

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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