Set it up
- 1
Turn on Firecrawl in your AI
In Claude: open Settings → Connectors and add Firecrawl. In ChatGPT: Settings → Apps & Connectors.
- 2
Add it to your app once
Copy the short config below into your app. It just tells your AI where to find Firecrawl.
- 3
Just ask
Tell it what you want in plain words — no special commands.
For example, say
“Crawl https://example.com and return clean markdown of the 5 most important pages”
Need the exact config? Show it +
Add to your client
{
"mcpServers": {
"firecrawl": {
"command": "npx",
"args": ["-y", "firecrawl-mcp"],
"env": {
"FIRECRAWL_API_KEY": "<your-firecrawl-api-key>"
}
}
}
}Paste into your client's MCP configuration file.
Quick skills
Copy one, paste it to your AI, watch it work.
Documentation Ingestion
“Crawl https://docs.example.com and return clean markdown for every page under /guides”
Structured Extraction
“Extract product name, price, and description from all product pages on example-shop.com”
Content Refresh
“Re-crawl our help center and return only pages that changed since last week”
Good to know
- · Firecrawl is usage-based — crawling a 1000-page site adds up fast
- · robots.txt and rate limits are respected — some sites return partial results
- · Crawl depth and include/exclude patterns matter — a broad crawl can be expensive
When to use
- ✓ You want to ingest a whole documentation site as AI context
- ✓ You need clean markdown from sites that are messy HTML
- ✓ You're building RAG and need bulk-cleaned content
- ✓ You want structured extraction (pricing, products, team members) from a site
When not to use
- × You need one page fetch — use fetch-mcp (simpler and free)
- × You're scraping at massive scale — use dedicated infrastructure
- × You need interactive scraping (clicks, forms) — use Puppeteer or Browserbase
About
Imagine asking your AI: 'Crawl this documentation site and give me clean markdown for every page' — and it turns any website into structured, LLM-ready content. This server connects your AI to Firecrawl, which crawls websites and returns clean markdown or structured data, skipping ads and navigation cruft.
The Firecrawl MCP server enables advanced web scraping and crawling through AI assistants. Crawl entire websites, extract structured content, convert pages to clean Markdown, and collect data at scale with built-in JavaScript rendering and anti-bot bypass.
Maintained by Firecrawl with a production API. The preferred choice for large-scale, reliable web data extraction.
Workflows That Use Firecrawl MCP
Works With
Also Consider
FAQ
What does Firecrawl MCP do? +
Imagine asking your AI: 'Crawl this documentation site and give me clean markdown for every page' — and it turns any website into structured, LLM-ready content. This server connects your AI to Firecrawl, which crawls websites and returns clean markdown or structured data, skipping ads and navigation cruft.
Do I need to know how to code? +
No. Turn it on in your AI's settings and ask in plain English — no terminal, no coding.
When should I use Firecrawl MCP? +
Reach for it when you need to: You want to ingest a whole documentation site as AI context; You need clean markdown from sites that are messy HTML; You're building RAG and need bulk-cleaned content; You want structured extraction (pricing, products, team members) from a site.
When should I avoid Firecrawl MCP? +
Skip it when: You need one page fetch — use fetch-mcp (simpler and free); You're scraping at massive scale — use dedicated infrastructure; You need interactive scraping (clicks, forms) — use Puppeteer or Browserbase.
How do I install Firecrawl MCP? +
In Claude Code, run: claude mcp add firecrawl -e FIRECRAWL_API_KEY=<your-key> -- npx -y firecrawl-mcp. Copy-paste configs for Claude Desktop, Cursor, and Windsurf are at the top of this page.
