RAG Docs

This MCP server, developed by qpd-v, enables AI assistants to perform semantic search and retrieval of documentation using a vector database (Qdrant). It provides tools for adding documentation from URLs, searching through stored content, and listing sources. The server implements web scraping, text chunking, and embedding generation using either Ollama or OpenAI. By connecting AI capabilities with vector search technology, this implementation empowers AI assistants to quickly find relevant information within large document collections. It is particularly useful for applications requiring context-aware information retrieval, knowledge base augmentation, or any scenario where an AI system needs to efficiently access and reason about domain-specific documentation.