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.
Exposes GitHub, SQLite database, and calendar tools, resources, and prompts over MCP so any MCP client can query data, manage issues, and schedule events.
Enables AI assistants and MCP-enabled clients to discover and call application capabilities exposed as structured, schema-defined tools, with input validation, error handling, and API/database integration. It also ships a sample client that demonstrates secure tool execution and seamless AI-agent interoperability.