No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by coleam00 · MCP Server · ★ 2.3k
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is mcp-crawl4ai-rag safe to install? View the security audit →
Crawl4AI RAG MCP Server Web Crawling and RAG Capabilities for AI Agents and AI Coding Assistants A powerful implementation of the Model Context Protocol (MCP) integrated with Crawl4AI and Supabase for providing AI agents and AI coding assistants with advanced web crawling and RAG capabilities. With this MCP server, you can scrape anything and then use that knowledge anywhere for RAG. The primary goal is to bring this MCP server into Archon as I evolve it to be more of a knowledge engine for AI coding assistants to build AI agents. This first version of the Crawl4AI/RAG MCP server will be improved upon greatly soon, especially making it more configurable so you can use different embedding models and run everything locally with Ollama. Consider this GitHub repository a testbed, hence why I haven't been super actively address issues and pull requests yet. I certainly will though as I bring this into Archon V2! Overview This MCP server provides tools that enable AI agents to crawl websites, store content in a vector database (Supabase), and perform RAG over the crawled content.
| Stars | 2,264 |
| Forks | 575 |
| Language | Python |
| Category | MCP Server |
| License | MIT |
| Quality Score | 73.2578538021368/100 |
| Open Issues | 56 |
| Last Updated | 2025-07-25 |
| Created | 2025-05-03 |
| Platforms | browser, mcp, python |
| Est. Tokens | ~18k |
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mcp-crawl4ai-rag is Web Crawling and RAG Capabilities for AI Agents and AI Coding Assistants. It is categorized as a MCP Server with 2.3k GitHub stars.
mcp-crawl4ai-rag is primarily written in Python.
You can find installation instructions and usage details in the mcp-crawl4ai-rag GitHub repository at github.com/coleam00/mcp-crawl4ai-rag. The project has 2.3k stars and 575 forks, indicating an active community.
mcp-crawl4ai-rag is released under the MIT license, making it free to use and modify according to the license terms.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
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