DataBridge

Integrates with DataBridge to enable ingestion and retrieval of contextual information from a local database, supporting persistent storage for AI applications.

This MCP server implementation provides a bridge to DataBridge, enabling AI assistants to ingest and retrieve information from a local database. Developed as part of the databridge-mcp project, it offers two main tools: one for ingesting user observations with metadata, and another for retrieving relevant information based on user queries. The server uses FastMCP for efficient request handling and is designed to work with Python 3.11+. It's particularly useful for AI applications requiring persistent storage and retrieval of contextual information, supporting use cases like maintaining conversation history or building knowledge bases from user interactions. The implementation focuses on simplicity and ease of integration, making it suitable for both development and production environments.