Crawl4ai Rag

Created By

coleam005 months ago

Overview

what is Crawl4AI RAG?

Crawl4AI RAG is a powerful MCP server that integrates web crawling and retrieval-augmented generation (RAG) capabilities for AI agents and coding assistants, enabling them to scrape web content and utilize it effectively.

how to use Crawl4AI RAG?

To use Crawl4AI RAG, clone the repository from GitHub, set up the necessary environment variables, and run the server using Docker or Python. You can then connect it to your AI applications for enhanced web crawling and content retrieval.

key features of Crawl4AI RAG?

Smart URL detection and recursive crawling
Parallel processing for efficient content scraping
Advanced RAG strategies including contextual embeddings and hybrid search
Knowledge graph integration for AI hallucination detection
Tools for searching code examples and validating AI-generated code

use cases of Crawl4AI RAG?

Enabling AI coding assistants to retrieve relevant documentation and code examples.
Enhancing AI agents with the ability to crawl and analyze web content.
Validating AI-generated code against real-world repositories to prevent hallucinations.

FAQ from Crawl4AI RAG?

Can Crawl4AI RAG handle all types of web content?

Yes! It is designed to crawl various types of web pages and extract relevant information.

Is there a specific setup required for using the knowledge graph features?

Yes, you need to set up Neo4j for the knowledge graph functionalities to work.

How can I customize the crawling and retrieval strategies?

You can configure various RAG strategies in the .env file before running the server.

Server Config

{
  "mcpServers": {
    "crawl4ai-rag": {
      "command": "python",
      "args": [
        "path/to/crawl4ai-mcp/src/crawl4ai_mcp.py"
      ],
      "env": {
        "TRANSPORT": "stdio",
        "OPENAI_API_KEY": "your_openai_api_key",
        "SUPABASE_URL": "your_supabase_url",
        "SUPABASE_SERVICE_KEY": "your_supabase_service_key",
        "USE_KNOWLEDGE_GRAPH": "false",
        "NEO4J_URI": "bolt://localhost:7687",
        "NEO4J_USER": "neo4j",
        "NEO4J_PASSWORD": "your_neo4j_password"
      }
    }
  }
}

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