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contextfetch-mcp

ContextFetch site crawl

contextfetch_crawl
Read-only

Crawl a website from a start URL and return its pages as Markdown, following same-site links up to a set depth and page limit. Add a query to rank pages and keep only relevant passages.

Instructions

Crawl one website from a start URL and get its pages as Markdown: same-site links only, up to max_depth hops (<= 3) and limit pages (<= 50), robots.txt obeyed. Pass query to rank the pages by relevance and return only their relevant passages. Costs 1 credit per page returned.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesPublic http(s) start URL.
limitNoMaximum pages to return (1-50, default 10).
queryNoOptional topic: ranks pages and prunes each to the relevant passages.
max_depthNoLink hops from the start page (0-3, default 1).
exclude_pathsNoRegexes; never follow links whose path matches one.
include_pathsNoRegexes; only follow links whose path matches one, e.g. ["^/docs/"].

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already cover the read-only/open-world profile, so the bar is lower; the description still adds billing behavior (1 credit per page returned), robots.txt compliance, and hard scope caps. Return format is disclosed as Markdown. It stops short of describing pagination or failure behavior, keeping it from a 5.

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 waste, front-loaded with what is retrieved before the constraints and optional query behavior. Every clause carries information.

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?

With no output schema, the description still names the return form (Markdown pages) and the credit cost, while the schema carries all parameter detail. An agent has enough to invoke and predict the result.

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 all six parameters, including the depth and limit bounds. The description repeats those caps and glosses the query ranking/pruning behavior, adding only marginal meaning beyond the 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?

States a specific verb (crawl) and resource (one website from a start URL) plus the output form (pages as Markdown). An agent can distinguish this from extract_url (single page) and map (link discovery) without opening either schema.

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?

Gives scoping conditions (same-site links only, robots.txt obeyed) and explains the query mode, which implies usage. But it never names an alternative sibling (e.g. extract_url or map) or states when NOT to crawl, leaving the agent to infer routing.

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