{"repo":"ToKiDoO/crawl4ai-rag-mcp","free":true,"listed":false,"github":"https://github.com/ToKiDoO/crawl4ai-rag-mcp","clone":"git clone https://github.com/ToKiDoO/crawl4ai-rag-mcp.git","description":"A self-contained MCP server in docker that combines the Crawl4AI, SearXNG, and Supabase to provide AI agents and coding assistants with complete web search, crawling, and RAG capabilities.","language":"Python","stars":46,"topics":[],"license":"MIT","category":"mcp-servers","readme_excerpt":"🐳 Crawl4AI+SearXNG MCP Server Web Crawling, Search and RAG Capabilities for AI Agents and AI Coding Assistants (FORKED FROM https://github.com/coleam00/mcp-crawl4ai-rag). Added SearXNG integration and batch scrape and processing capabilities. A self-contained Docker solution that combines the Model Context Protocol (MCP), Crawl4AI, SearXNG, and Supabase to provide AI agents and coding assistants with complete web search, crawling, and RAG capabilities . 🚀 Complete Stack in One Command : Deploy everything with docker compose up -d - no Python setup, no dependencies, no external services required. 🎯 Smart RAG vs Traditional Scraping Unlike traditional scraping (such as Firecrawl) that dumps raw content and overwhelms LLM context windows, this solution uses intelligent RAG (Retrieval Augmented Generation) to: - 🔍 Extract only relevant content using semantic similarity search - ⚡ Prevent context overflow by returning focused, pertinent information - 🧠 Enhance AI responses with precisely targeted knowledge - 📊 Maintain context efficiency for better LLM performance Flexible Output Options: - RAG Mode (default): Returns semantically relevant chunks with similarity scores - Raw Markdown Mode : Full content extraction when complete context is needed - Hybrid Search : Combines semantic and keyword search for comprehensive results 💡 Key Benefits - 🔧 Zero Configuration : Pre-configured SearXNG instance included - 🐳 Docker-Only : No Python environment setup required - 🔍 Integrat","default_branch":null,"files":null,"tree":[],"storefront":"/r/ToKiDoO","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ToKiDoO/crawl4ai-rag-mcp/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}