Loading tool details…
Open-source, LLM-friendly Python web crawler and scraper that emits clean Markdown, JSON, and extracted structured data — with an MCP server so agents can crawl directly. MIT-licensed and free.
Open-source, LLM-friendly Python web crawler and scraper that emits clean Markdown, JSON, and extracted structured data — with an MCP server so agents can crawl directly. MIT-licensed and free.
Crawl4AI (unclecode/crawl4ai on GitHub) is one of the most popular open-source web crawlers built specifically for feeding LLMs and RAG pipelines. Instead of dumping raw HTML, it produces clean Markdown, structured JSON, and screenshots in a single pass, so the output plugs straight into a vector store or a context window without extra parsing. It ships as a Python library (pip install crawl4ai), a Docker image, and — as of the AsyncWebCrawler line — a full async engine that handles JavaScript-heavy pages via Playwright under the hood.
The features that matter for real agents: adaptive crawling that stops once it has enough content, dispatchers that stream results as pages finish (great for long crawls), multiple extraction strategies (CSS selectors, XPath, LLM-based schema extraction, cosine similarity), stealth mode with proxy rotation, hooks/auth for logged-in sessions, and crash recovery so a broken crawl can resume without redoing the whole job. In 2026 the project shipped a built-in MCP server, which means Claude Desktop or any MCP-compatible agent client can crawl and scrape directly through tool calls — no bespoke integration glue.
Crawl4AI is MIT-licensed and free to self-host; the only costs are your own compute and any paid proxy service you plug in. It has 40k+ GitHub stars, active weekly releases, and is used inside RAG stacks and agent frameworks that need a scraper they can control. Compared with hosted options like /tools/firecrawl or /tools/apify, you trade managed infrastructure for zero per-page fees and full control over extraction, browser fingerprinting, and where data ends up.
Free
Ready to get started with Crawl4AI?
View Pricing Options →Crawl4AI works with these platforms and services:
We believe in transparent reviews. Here's what Crawl4AI doesn't handle well:
Recent releases have expanded Crawl4AI well beyond a basic scraper. The MCP server is now a first-class feature, allowing Claude Desktop and other MCP clients to use Crawl4AI as a callable tool. Adaptive crawling intelligently halts when enough information has been gathered, and link preview with scoring prioritizes the most relevant URLs during deep crawls. A new regex-based extraction strategy delivers zero-LLM extraction for common patterns at high speed. Virtual scroll support now handles infinite feeds like Twitter, Instagram, and TikTok, and the library has added PDF processing, improved stealth mode, persistent identity profiles, and a memory-adaptive dispatcher for large parallel jobs. The Docker deployment exposes a FastAPI interface with streaming endpoints, and crash-recovery improvements make multi-hour crawls more reliable in production RAG pipelines.
Web Scraping
Web scraping, crawling, and search API that turns any website into clean Markdown or structured data for AI agents and LLMs.
Search & Discovery
ScrapingBee is a web scraping API for fetching pages without managing proxies, browsers, or anti-bot defenses. It supports JavaScript rendering, AI-assisted extraction, Markdown and JSON outputs, screenshots, dedicated scraper APIs, and integrations for automation and AI workflows.
Web Data & Scraping
The largest marketplace of ready-to-run web scrapers (Apify calls them Actors) with an MCP server so AI agents can pull live web data on demand.
Pricing and features change often. If anything on this Crawl4AI page is wrong or missing, tell us and include a link to the source. We review every correction.