An educational MCP server example built with FastMCP that demonstrates how to expose tools, resources, and prompts to AI clients. Provides a learning foundation for building MCP servers with Python and integrating them with AI applications like IDEs and chatbots.
Provides a template for building an MCP server with example tools, prompts, and resources, enabling developers to create a server that exposes data and actions to AI clients.
Enables learning and integration testing of the Model Context Protocol by evolving from a minimal server toward production-grade tools, resources, prompts, and agent interoperability.
Enables AI agents to access unified development tools including code generation, documentation synchronization, test case rendering, and architecture graph queries through a single MCP server.