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unclecode/crawl4ai

📈 Trending65,842PythonAudience · developerComplexity · 3/5ActiveLicenseSetup · moderate

TLDR

Web crawler that converts pages to clean Markdown for AI systems, handling JavaScript and stripping noise automatically.

Mindmap

mindmap
  root((Crawl4AI))
    What it does
      Fetches web pages
      Converts to Markdown
      Strips ads and noise
      Handles JavaScript
    How it works
      Playwright browser
      Async pool
      Session management
      Proxy rotation
    Use cases
      Feed AI pipelines
      Build RAG systems
      Scrape for research
      Populate knowledge bases
    Tech stack
      Python
      Playwright
      Docker support
    Extraction modes
      Clean Markdown
      Structured schemas
      Natural language Q&A

Things people build with this

USE CASE 1

Feed live web data into AI retrieval-augmented generation (RAG) systems and autonomous agents.

USE CASE 2

Scrape competitor websites and online documentation for research and knowledge base population.

USE CASE 3

Extract structured data from JavaScript-heavy websites using natural language questions or custom schemas.

USE CASE 4

Build data pipelines that convert messy web content into clean, AI-ready Markdown automatically.

Tech stack

PythonPlaywrightDockerAsync

Getting it running

Difficulty · moderate Time to first run · 30min

Requires Docker or local Playwright browser installation; async setup needs Python 3.7+.

Use freely for any purpose including commercial. Keep the notice and disclose changes to the patent grant.

In plain English

Crawl4AI is an open-source web crawling and scraping library specifically designed to produce output that is easy for AI systems to consume. The core problem it solves is that most web pages contain a lot of noise, navigation menus, ads, footers, scripts, and AI tools like large language models work best with clean, well-structured text. Crawl4AI fetches web pages and converts them into clean Markdown format, stripping away the clutter so the content can feed directly into AI workflows like retrieval-augmented generation (RAG), autonomous agents, or data analysis pipelines. Under the hood it uses an async browser pool built on Playwright (a browser automation library) to render pages just like a real browser would, which means it handles JavaScript-heavy sites that simple HTTP scrapers miss. It supports features like session management, proxy rotation, cookie handling, anti-bot detection bypass, and deep crawling strategies such as breadth-first search across multiple pages. Content can be extracted as clean Markdown, or developers can instruct the crawler to extract structured data by providing a schema or asking an AI model a natural language question about the page. It can be run from a Python script, a command-line interface, or inside a Docker container with no API key required. You would use Crawl4AI when building an AI pipeline that needs live web data, when scraping competitor sites for research, or when populating a knowledge base from online documentation. The tech stack is Python with Playwright for browser automation, installable via pip.

Copy-paste prompts

Prompt 1
Show me how to use Crawl4AI to crawl a website and convert its pages to Markdown for feeding into an LLM.
Prompt 2
How do I set up Crawl4AI with proxy rotation and session management to scrape multiple pages without getting blocked?
Prompt 3
Write a Python script using Crawl4AI to extract structured data from a webpage by asking it a natural language question.
Prompt 4
How can I run Crawl4AI in Docker and use it to populate a knowledge base from a documentation site?
Prompt 5
Show me how to use Crawl4AI's breadth-first search to crawl an entire website and extract all product information.
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Generated 2026-05-18 · Model: sonnet-4-6 · Verify against the repo before relying on details.