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 minimal, decorator-based framework for building MCP servers in Python with zero dependencies. It enables you to define tools and resources via simple decorators, handling JSON-RPC protocol, type inference, and stdio transport automatically.
A robust server implementing the Model Context Protocol with SSE and STDIO transport, enabling real-time communication and extensible tooling for AI models.
A foundation for building custom local Model Context Protocol (MCP) servers that provide tools accessible to AI assistants like Cursor or Claude Desktop.
A streamlined foundation for building Model Context Protocol servers in Python, designed to make AI-assisted development of MCP tools easier and more efficient.
