Crawl4AI
Crawl4AI provides an open-source, asynchronous web crawler and scraper designed for LLM-friendly data extraction, now also available as a hosted cloud API. The platform's adaptive crawling technology uses a three-layer scoring system—coverage, consistency, and saturation—to automatically stop when sufficient information has been gathered, preventing both over- and under-crawling. The hosted API turns any URL into clean Markdown, typed JSON, or search results, with support for MCP integration into coding agents like Claude Code and Cursor.
- Developer Tools
- Artificial Intelligence
- Software Only
- AI Agents
Funding
Founders
Founder details are not available yet.
Product
Problem
Traditional web crawlers follow predetermined patterns, often over-crawling by fetching irrelevant pages or under-crawling by stopping too early, leading to wasted resources and incomplete data. This inefficiency is particularly problematic for AI and LLM applications that require precise, relevant, and comprehensive web content for training, retrieval-augmented generation, and other data-intensive tasks.
Solution
Crawl4AI provides an open-source, asynchronous web crawler and scraper specifically designed for LLM-friendly data extraction, now also available as a hosted cloud API. The platform's core innovation is its adaptive crawling technology, which uses a three-layer scoring system—coverage, consistency, and saturation—to determine when enough information has been gathered, automatically stopping the crawl to save time and resources. It supports both a fast, free statistical strategy for exact-term queries and a more nuanced embedding strategy that uses semantic understanding for complex or ambiguous topics. Developers can configure confidence thresholds, page limits, and link-following behavior, and the tool outputs clean markdown, making it easy to feed into AI models. The hosted API turns any URL into clean Markdown, typed JSON, or search results with no infrastructure setup required, and is accessible via HTTP, MCP, or directly within coding agents like Claude Code and Cursor.
Target Audience
Primary users are developers, data scientists, and AI engineers building LLM-powered applications, RAG systems, and research tools that require efficient, accurate, and large-scale web data extraction.
Features
- Adaptive crawling with three-layer scoring (coverage, consistency, saturation) to automatically stop when information sufficiency is reached
- Dual-strategy support: statistical (fast, free, term-based) and embedding (semantic, using models like sentence-transformers/all-MiniLM-L6-v2) for different query types
- Configurable parameters including confidence threshold, max pages, top-k links, and minimum gain threshold for fine-tuned control
- Asynchronous architecture (AsyncWebCrawler) for high-concurrency, efficient web scraping
- Hosted cloud API with three global regions (EU, Singapore, US), automatic engine selection (cache → HTTP → browser), and support for residential/ISP proxies
- Scrape endpoint returning clean Markdown/HTML with optional parsing of links, media, metadata, and tables; batch mode for up to 50 URLs and background jobs for up to 10,000 URLs
- Search endpoint with ranked results and optional rich blocks including follow-up questions, related queries, entity cards, and news
- MCP server support for integration into Claude Code, Codex, Cursor, Gemini CLI, and other agent-based workflows