Implements a Model Context Protocol (MCP) server for Retrieval-Augmented Generation (RAG) applications, supporting Qdrant and Chroma vector databases.
Vito provides a robust Model Context Protocol (MCP) server implementation designed to enhance Retrieval-Augmented Generation (RAG) applications. Seamlessly integrate with Qdrant or Chroma vector databases to store and retrieve domain knowledge, leveraging Qdrant's FastEmbed for efficient embedding generation. Vito streamlines the process of managing and accessing relevant information, enabling AI models to provide more informed and context-aware responses. It offers a straightforward setup, comprehensive documentation, and flexibility to adapt to various AI IDE integrations, empowering developers to build advanced knowledge-driven applications.
Key Features
01Supports Qdrant and Chroma vector databases
02Supports storing documentation files (PDF, TXT) with metadata
03Enables domain knowledge storage and retrieval
040 GitHub stars
05Uses Qdrant's built-in FastEmbed for embedding generation
06Configurable database selection via environment variables
Use Cases
01Enhancing AI IDEs with knowledge server capabilities (Cursor AI, Claude Desktop)
02Building RAG applications with efficient knowledge retrieval
03Integrating domain knowledge into AI models for more accurate responses
