How is crawling different from scraping a single page?

Scraping fetches one URL you already have. Crawling starts at a URL and follows its links to reach many pages, so the agent can ingest a whole documentation site or section without listing every page first. Crawls run asynchronously: you start a job and poll for results as pages finish.

How do I keep a crawl from pulling the whole internet?

Bound it. Limit the crawl to a path, a page count, or a link depth so it stays on the section you care about. Firecrawl and ScrapeGraph expose status and stop controls, so an agent can watch a job and halt it if it grows beyond what the task needs.

MCP servers that can crawl a website

3 verified servers expose a tool that can crawl a website

Scraping one page is a single fetch. Crawling is the harder job: start at a URL, follow links across a whole site, and bring back every page as clean text the model can read. It is how an agent turns a documentation site or a catalog into something it can reason over.

These verified servers let an agent crawl a website, not just a single page.

Top pick

Firecrawl

Official

Official Firecrawl server that turns any website into clean, LLM-ready data through scrape, crawl, map, search, and extract.

search-and-data6,500

Tools:

firecrawl_crawl
firecrawl_check_crawl_status

firecrawl_crawl starts an asynchronous crawl that turns a site into clean markdown, and firecrawl_check_crawl_status polls the job and returns pages as they complete, the most complete crawl flow here.

Pick 2

ScrapeGraphAI

Official

ScrapeGraphAI's official MCP server: AI-powered scraping, structured extraction, web search, multi-page crawling, and scheduled page-change monitoring.

search-and-data

Tools:

crawl_start
crawl_get_status

ScrapeGraph starts a multi-page crawl with crawl_start and polls it with crawl_get_status, and adds crawl_stop and crawl_resume so an agent can pause or halt a long run.

Pick 3

Tavily

Official

Official Tavily server giving agents real-time web search, page extraction, site crawling, and site mapping built for AI.

search-and-data2,100

Tool:

tavily-crawl

tavily-crawl follows links from a starting URL to gather a site's content in one call, shaped for feeding the pages straight into an agent's retrieval loop.

What to know

A crawl is asynchronous by nature, because a site has many pages and fetching them takes time. That shapes how these tools work: the agent starts a job and then polls for results rather than waiting on one call. Firecrawl's firecrawl_crawl kicks off the job and firecrawl_check_crawl_status returns progress and pages as they finish; ScrapeGraph splits the same pattern across crawl_start and crawl_get_status, with crawl_stop and crawl_resume to control a run in flight. Tavily's tavily-crawl follows links from a starting URL in a single tool built for feeding an agent's retrieval.

The practical limits are scope and politeness. Point a crawl at a whole domain and it can pull thousands of pages, most of which the task does not need, so bound it by path or depth. And a site crawled last week rarely needs a full re-crawl; knowing what was already fetched, and when, saves the run from re-reading ground it has covered.

Questions

How is crawling different from scraping a single page?: Scraping fetches one URL you already have. Crawling starts at a URL and follows its links to reach many pages, so the agent can ingest a whole documentation site or section without listing every page first. Crawls run asynchronously: you start a job and poll for results as pages finish.
How do I keep a crawl from pulling the whole internet?: Bound it. Limit the crawl to a path, a page count, or a link depth so it stays on the section you care about. Firecrawl and ScrapeGraph expose status and stop controls, so an agent can watch a job and halt it if it grows beyond what the task needs.