mcp-ragdocs

Provides vector-based semantic search and real-time context augmentation for AI assistants by retrieving and processing documentation from multiple sources using Model Context Protocol.

Provides vector-based semantic search and real-time context augmentation for AI assistants by retrieving and processing multiple documentation sources through the Model Context Protocol.

Provides up-to-date, version-aware documentation indexing and advanced semantic search via the Model Context Protocol to enhance AI coding assistants with accurate, reliable, and private access to official code references from multiple sources.

Enables semantic search and natural language retrieval of documentation by indexing content from URLs or local files into a vector database using Model Context Protocol integration.

Provides tools for retrieving, managing, and processing documentation via vector search to enhance AI assistant responses with relevant, context-aware information using the Model Context Protocol.