Firecrawl is an AI-native web data platform that converts any website into clean, structured, LLM-ready data with a single API call. Designed specifically for AI agents and Retrieval-Augmented Generation (RAG) pipelines, Firecrawl handles the messy reality of the modern web — JavaScript-heavy SPAs, dynamic content, anti-bot protections, rate limits, and PDFs — so developers do not have to maintain custom scraping infrastructure. The platform offers four core endpoints: Scrape (single-URL extraction to Markdown or structured JSON), Crawl (automatic full-site traversal with depth and pattern controls), Map (lightning-fast sitemap discovery returning every URL on a domain), and Extract (LLM-powered structured data extraction from natural-language schemas). Firecrawl includes built-in browser rendering, proxy rotation, smart caching, robots.txt compliance, and content cleaning that strips ads, navigation, and boilerplate before output. Native SDKs are available for Python, Node.js, Go, and Rust, with first-class integrations for LangChain, LlamaIndex, CrewAI, Dify, n8n, and Zapier. Open-sourced under the AGPL license with a generous free tier and a popular self-hosted option, Firecrawl has become the default web data layer for thousands of AI startups, enterprise RAG systems, and autonomous agent platforms in 2026.