Firecrawl
Power AI agents with clean web data
About Firecrawl
Firecrawl solves the least glamorous problem in agent engineering: the web is written for browsers, and models need text. It takes a URL and returns clean markdown or structured JSON, handling the JavaScript rendering, pagination, anti-bot friction and document parsing that turn a two line scraping script into a fortnight of maintenance. That single capability has made it the default primitive underneath most agent frameworks that need live web context rather than a training corpus frozen at some past date.
The scale is the argument. The repository carries over 169,000 GitHub stars, up from roughly 48,000 earlier in 2026, and the company reports more than 1.25 million developers across 150,000 companies, naming Shopify, Canva and Apple among users. First party SDKs cover Python, Node.js, Go, Rust, Java and Elixir, and an MCP compatible server drops the whole toolset into Claude Code, Cursor and similar agents so a coding assistant can fetch live pages mid conversation. The core is AGPL-3.0 and genuinely self hostable, with a hosted cloud for teams that would rather not run the proxy and rendering infrastructure themselves.
Pick the verb that matches the job. Scrape takes one URL and returns markdown, JSON, HTML or a screenshot. Crawl follows links across an entire site without needing a sitemap, respecting robots.txt as it goes. Map enumerates the URLs a site exposes, which is the cheap way to understand a target before spending credits on it. Search runs a web query and returns full page content rather than the list of links a search API would give you, collapsing two steps into one. Interact clicks, navigates and operates pages programmatically when the data sits behind a multi step UI. Parse extracts content from documents including PDF and DOCX. Monitor watches pages for changes over time. Each is one API call, billed in credits, and available through the SDK for your language or through the MCP server if you would rather call it from inside an agent. Self hosting under AGPL-3.0 is a supported path if you want to run it on your own infrastructure.
- •Scrape - Convert a single URL into clean markdown, JSON, HTML or a screenshot
- •Crawl - Follow links across an entire site without requiring a sitemap, respecting robots.txt
- •Search - Return full page content for a web query in one call rather than just result links
- •Interact - Click, navigate and operate pages programmatically for extraction behind a multi step UI
- •Map - Enumerate the URLs available on a site before committing to a full crawl
- •Monitor - Track changes to web content over time
- •Parse - Extract data from documents including PDF and DOCX
- •First Party SDKs - Official libraries for Python, Node.js, Go, Rust, Java and Elixir
- •MCP Server - Callable from Claude Code, Cursor and other agents mid conversation
- •Self Hostable - AGPL-3.0 core you can run on your own infrastructure
Anyone building an agent, a RAG pipeline or a data product that needs current web content. It is most valuable to small teams, because the work it replaces (headless browser fleets, proxy rotation, parser maintenance) is exactly the sort of infrastructure that quietly consumes an engineer. Teams with strict data handling requirements can self host rather than routing content through a third party. The MCP server suits developers who want their coding agent to read documentation and live pages during a session. Two caveats worth stating: the business sits on top of scraping other people's sites, which is permanently exposed to anti-bot escalation and legal pressure, and at this scale it is an established tool rather than an emerging one.
Pricing
$0 - $599/mo
Billed annually, no monthly price published
- Free$0/mo
- Hobby$16/mo
- Standard$83/mo
- Growth$333/mo
- Scale$599/mo
- EnterpriseContact sales
From the vendor pricing page, 2026-09-21
