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zapfetch

ZapFetch MCP Server

by zapfetch

zapfetch_crawl

Crawl a website to gather content from multiple pages. Returns a job ID for async polling. Best for whole-site extraction; for single pages use scrape, for URL discovery use map.

Instructions

Crawl a website and extract content from multiple pages. Use this when the user wants to gather content from an entire site or section. Returns a job_id for async polling. Long-running — consider asking the user before invoking if the site is large. For a single page, use zapfetch_scrape. For URL discovery only (no content), use zapfetch_map.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesThe root URL to start crawling from
limitNoMaximum pages to crawl (default 50)
maxDiscoveryDepthNoMaximum link depth from root URL
includePathsNoOnly crawl URLs matching these path patterns (regex)
excludePathsNoSkip URLs matching these path patterns (regex)
crawlEntireDomainNoCrawl entire domain, not just subpath of root URL
Behavior5/5

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

Despite no annotations, the description clearly states it is long-running and returns a job_id for async polling. It also advises considering user consent for large sites, which covers important behavioral aspects.

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?

Concise, with key information front-loaded. Every sentence adds value: defines the tool, specifies async nature, warns about runtime, and gives alternatives. No 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?

Given the tool's complexity (crawling, async, multiple parameters), the description covers purpose, usage boundaries, behavioral notes, and alternatives. No output schema needed since it returns a job_id; the polling tool likely handles that.

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

Parameters4/5

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

Schema description coverage is 100%, so baseline is 3. The description does not repeat param details but adds context by explaining the overall behavior (async) and when to use. Since all parameters are well-documented in schema, the description adds value indirectly.

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 clearly states it crawls a website and extracts content from multiple pages, using specific verbs ('crawl', 'extract'). It distinguishes from siblings: 'For a single page, use zapfetch_scrape. For URL discovery only (no content), use zapfetch_map.'

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?

Explicitly tells when to use (multi-page content gathering) and when not to (single page -> zapfetch_scrape, URL discovery -> zapfetch_map). Also warns about long-running nature and suggests asking user before invoking on large sites.

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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