mcp-ragdocsAn MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation contex

RAG Documentation MCP Server is an implementation providing tools for retrieving and processing documentation through vector search. This enables AI assistants to augment their responses with relevant documentation context. The server features vector-based search and retrieval, support for multiple sources, semantic search capabilities, and automated documentation processing. It also offers real-time context augmentation for large language models. Three primary tools are provided: search_documentation, which enables searching through stored documentation using natural language queries; list_sources, which lists all documentation sources currently stored in the system; and remove_documentation, which removes specific documentation sources from the system by their URLs. Additionally, the server includes a queue management system for processing new documentation sources. Users can configure the server for use with tools like Claude Desktop, and it is designed for enhancing AI responses, building documentation-aware AI assistants, creating context-aware tooling for developers, implementing semantic documentation search, and augmenting existing knowledge bases