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contextfetch-mcp

ContextFetch URL to Markdown

contextfetch_extract_url
Read-only

Fetch a public web page as clean Markdown with tables kept; pass a query to return only the passages relevant to it instead of the whole page.

Instructions

Fetch a public web page (docs, articles, GitHub files, arXiv papers) as clean Markdown with tables preserved. Pass query to get only the passages relevant to it instead of the whole page.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic http(s) URL to read.
queryNoOptional question or topic; returns only the relevant passages.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety and open-world scope are covered. The description adds useful behavior — Markdown conversion with table preservation and a filtering mode that shrinks the response — but says nothing about limits, truncation, or what happens on JS-rendered or paywalled pages.

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 sentences, zero filler, with the core capability front-loaded and the optional mode explained second. Nothing could be cut without losing information.

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?

For a two-parameter, annotated, read-only fetch tool, the description covers purpose, content types, output shape, and the optional filtering mode — enough to call it correctly. The remaining gap is operational edge cases, which matters somewhat given the open-world hint but is not required to invoke it.

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 both parameters are already documented in the schema. The description's explanation of `query` (returns only relevant passages instead of the whole page) is a slight reframing rather than new semantics; `url` gets only the implicit 'must be public' constraint already in the schema.

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 (fetch a public web page) and names concrete content archetypes (docs, articles, GitHub files, arXiv papers) plus the output format (clean Markdown, tables preserved). It does not distinguish itself from the nearby crawl/map siblings, so an agent must still infer that this is the single-page reader.

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 second sentence establishes a clear conditional: pass `query` for relevant passages instead of the whole page, which is genuine usage guidance for that parameter. There is no explicit 'use this instead of X' routing against siblings such as contextfetch_crawl or contextfetch_search, and no stated when-not conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.