Firecrawl
Firecrawl is an open-source context API that helps AI agents and LLM applications search, scrape, crawl, map, and interact with the web at scale, returning clean Markdown, JSON, screenshots, metadata, and structured data.
Overview
Firecrawl helps AI systems turn messy, dynamic websites into structured machine-usable context for RAG pipelines, deep research agents, AI chatbots, data enrichment, competitive intelligence, onboarding, monitoring, and agentic web workflows.
Core Features & Capabilities
Ideal for AI engineers, LLM app builders, RAG developers, AI agent teams, data engineers, market research teams, lead generation teams, competitive intelligence teams, search product teams, developer-tool builders, automation teams, AI chatbot builders, startups, enterprise AI teams, and developers who need reliable web context inside AI workflows.
- Search the web and receive full-page content that is already converted into usable Markdown for AI agents and RAG pipelines
- Scrape individual pages into Markdown, HTML, screenshots, metadata, or structured JSON using custom schemas
- Crawl entire websites or sections with depth, page limits, path filters, and reliable JavaScript rendering
- Interact with complex pages by clicking, scrolling, typing, waiting, pressing, navigating, and extracting data through browser actions
- Connect Firecrawl to agents, MCP clients, CLI workflows, SDKs, RAG systems, research agents, and lead-enrichment pipelines
Trending Use Cases
Why Developers Choose Firecrawl
Visit the Firecrawl website or docs to explore the API, playground, pricing, SDKs, CLI, MCP server, and open-source repository. Developers can start with the hosted API, install the Python or Node SDK, call search or scrape endpoints, return Markdown for quick LLM context, add JSON schemas for structured extraction, or use crawl and interact for larger and more complex sites. AI agent teams can connect Firecrawl through MCP or CLI setup commands so agents can search, scrape, and interact with the web directly.
“Firecrawl turns the live web into clean context for AI systems, combining search, scrape, crawl, interact, and structured extraction in one developer API.”
Getting Started with Firecrawl
By combining web search, scraping, crawling, page interaction, JavaScript rendering, document parsing, structured extraction, Markdown output, screenshots, MCP tools, CLI workflows, SDKs, and open-source infrastructure, Firecrawl gives AI builders a practical way to turn live web content into clean context for agents and LLM applications.
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Firecrawl
Firecrawl is the creator of an open-source web data platform and hosted context API for AI agents, offering search, scrape, crawl, map, interact, Markdown conversion, structured JSON extraction, JavaScript rendering, MCP integration, SDKs, and LLM-ready web data infrastructure.
Firecrawl is a developer-first web data infrastructure platform for AI agents, RAG systems, search products, research agents, lead enrichment tools, and LLM applications that need reliable access to live web data. It provides a unified API for searching the web, scraping pages, crawling sites, mapping URLs, extracting structured data with schemas, rendering JavaScript-heavy pages, parsing PDFs and documents, capturing screenshots, and interacting with pages through actions such as click, scroll, type, wait, press, and navigate. Firecrawl is open source, available as a hosted API, and integrates with AI agents through MCP, CLI workflows, SDKs, and agent skills for tools such as Cursor, Claude Code, Windsurf, Codex, OpenAI, and Gemini.
www.firecrawl.dev/
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