A boilerplate template for developing Model Context Protocol (MCP) servers, providing a structured framework for defining tools, resources, and prompts.
Embeds a secure, curated MCP server inside Python applications, exposing explicit tools, resources, and prompts with dependency injection, security policies, and in-memory testing.
Enables serving a remote Model Context Protocol endpoint by exposing tools, prompts, and resources with customizable authorization and hooks, allowing AI models to interact with your application through a standardized JSON-RPC interface.