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Firecrawl
Turn any website into clean, LLM‑ready data instantly
Firecrawl provides a fast API that scrapes, crawls, maps, and extracts websites into clean markdown, HTML, or structured data, handling dynamic content and anti‑bot protections.
Overview
Overview
Firecrawl is an API‑first service that transforms any public website into LLM‑ready formats such as markdown, HTML, screenshots, and structured JSON. It can scrape a single page, crawl an entire site (including subpages), map all discovered URLs, and run AI‑powered extraction to pull out tables, lists, or custom data structures. The platform also offers change‑tracking, allowing you to monitor updates over time.
Who it's for and how to deploy
Developers building Retrieval‑Augmented Generation (RAG) bots, data scientists gathering web corpora, and low‑code platform creators can integrate Firecrawl via its documented SDKs (Python, Node) or through LangChain, LlamaIndex, and other LLM frameworks. While a hosted version is production‑ready, the repository can be run locally for experimentation, though full self‑hosting is still under development. Integration points include Zapier, Pabbly Connect, and community SDKs for Go and Rust, making it easy to embed web data extraction into existing workflows.
Highlights
Multi‑format scraping (markdown, HTML, screenshots, structured data)
Full‑site crawling with depth control and async batch jobs
AI‑powered extraction and change tracking
Robust handling of anti‑bot measures, JS rendering, and custom headers
Pros
- LLM‑ready output formats
- Supports dynamic and protected sites
- Scalable async batch endpoint
- Extensive SDK and low‑code integrations
Considerations
- Self‑hosting still in development
- Reliance on external API for production use
- Limited on‑premise documentation
- Potential cost for high‑volume usage
Managed products teams compare with
When teams consider Firecrawl, these hosted platforms usually appear on the same shortlist.
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Fit guide
Great for
- Developers building RAG or chatbot applications
- Data scientists needing clean web corpora
- Low‑code platform creators integrating web data
- Teams requiring change monitoring of websites
Not ideal when
- Environments that must keep all processing offline
- Projects with strict budget constraints on API calls
- Simple static page scraping where a basic HTTP client suffices
- Users needing full CMS export features not listed
How teams use it
Chatbot with up‑to‑date website knowledge
Generates accurate answers using the latest site content fetched in markdown
Automated market research
Extracts product specifications and pricing across competitor sites for analysis
Content summarization pipeline
Converts articles to clean markdown for downstream LLM summarization
Website change alerts
Detects and notifies when key pages are updated, enabling timely actions
Tech snapshot
TypeScript72%
Python20%
Rust6%
Astro1%
JavaScript1%
Jupyter Notebook1%
Frequently asked questions
Do I need an API key to use Firecrawl?
Yes, you must sign up on Firecrawl and obtain an API key for authenticated requests.
Can I self‑host the service?
Local execution is possible for testing, but full self‑hosting is still under development.
What output formats are supported?
Markdown, HTML, screenshots, and structured JSON data are available, plus metadata extraction.
How does Firecrawl handle JavaScript‑rendered pages?
The service includes a headless browser layer that renders dynamic content before extraction.
Is there a usage limit or credit system?
Usage is tracked via credits per request; limits depend on your subscription plan.
Project at a glance
Active- Stars
- 76,406
- Watchers
- 76,406
- Forks
- 5,790
LicenseAGPL-3.0
Repo age1 year old
Last commit4 hours ago
Primary languageTypeScript
Last synced 3 hours ago