文章摘要
FastMCP facilitates the conversion of knowledge graphs into Model Context Protocol (MCP) servers, significantly expanding the contextual understanding of AI assistants. This framework allows AI models, such as Claude, to directly query and retrieve structured information from enterprise knowledge bases. The implementation involves setting up a Flask-based server to implement MCP specifications, acting as an intermediary between the AI assistant and the underlying graph database. By providing AI assistants with a standardized way to access a company's unique data, FastMCP enhances their ability to generate accurate, relevant, and contextually rich responses for complex queries, streamlining AI assistant access to dynamic, external knowledge.