A universal framework for creating and deploying custom Model Context Protocol (MCP) tool servers with decorator-based tool registration, supporting multiple transports and automatic JSON schema generation for AI assistants.
A Django MCP server that exposes tools and resources to AI agents using simple decorators, with auto-discovery, type safety, and custom authentication.
A lightweight server implementation that exposes Python functions as discoverable tools via HTTP using the Machine-to-Machine Communication Protocol (MCP). Enables remote execution of Python functions through a JSON-RPC interface with async support and type safety.
Enables building and running MCP servers over streamable HTTP, exposing tools to AI assistants like Cursor, with examples of mounting multiple servers in FastAPI.
A Python implementation of the MCP server that enables AI models to connect with external tools and data sources through a standardized protocol, supporting tool invocation and resource access via JSON-RPC.