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Veeam has unveiled an integration of the Model Context Protocol (MCP) to enhance AI-driven data access and understanding for its data management platform. * This development enables AI assistants to intelligently interact with and leverage enterprise data managed by Veeam's backup and recovery solutions. * MCP provides a standardized, efficient method for AI models to request and receive relevant contextual information directly from external data systems and applications. * The integration aims to streamline data interaction for AI-powered applications, significantly improving data accessibility and operational efficiency within complex data environments. * It positions Veeam's platform as a crucial, context-rich data source for AI agents seeking precise, real-time information from protected data.
The article details the process of building and deploying a Model Context Protocol (MCP) server, designed to provide external tool access and context for AI assistants. * It demonstrates setting up a simple MCP server using Heroku and Python, focusing on managing context and tool definitions. * The guide shows how to integrate this custom MCP server with the Cursor AI code editor, allowing Cursor to leverage the server's defined tools and context. * The example MCP server includes a tool for fetching information from a GitHub repository, illustrating how AI can interact with external systems. * The server's setup involves using FastAPI for the web service and defining a custom `ToolLoader` for dynamic tool discovery.