🚀 Nchan MCP Transport
The best way to deploy mcp server. A high-performance WebSocket/SSE transport layer & gateway for Anthropic's MCP (Model Context Protocol) — powered by Nginx, Nchan, and FastAPI.
What is 🚀 Nchan MCP Transport?
What is Nchan MCP Transport? Nchan MCP Transport is a high-performance WebSocket/SSE transport layer and gateway designed for Anthropic's Model Context Protocol (MCP), enabling real-time, scalable AI integrations with Claude and other LLM agents. How to use Nchan MCP Transport? To use Nchan MCP Transport, install the server SDK with pip install httmcp, run the demo in Docker, and define your tools using Python decorators. Key features of Nchan MCP Transport? Dual Protocol Support: Supports WebSocket and SSE with automatic detection. High Performance Pub/Sub: Built on Nginx + Nchan, handling thousands of concurrent connections. MCP-Compliant Transport: Fully implements Model Context Protocol (JSON-RPC 2.0). OpenAPI Integration: Auto-generate MCP tools from any OpenAPI spec. Tool / Resource System: Register tools and resources using Python decorators. Asynchronous Execution: Background task queue with live progress updates. Dockerized Deployment: Easily deployable with Docker Compose. Use cases of Nchan MCP Transport? Building Claude plugin servers over WebSocket/SSE. Creating real-time LLM agent backends. Connecting Claude to internal APIs via OpenAPI. Serving as a high-performance tool/service bridge for MCP. FAQ from Nchan MCP Transport? What are the requirements for Nchan MCP Transport? Requires Nginx with Nchan module, Python 3.9+, and Docker/Docker Compose. Is it easy to deploy? Yes! It can be easily deployed using Docker Compose.
As an MCP (Model Context Protocol) server, 🚀 Nchan MCP Transport enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.
How to use 🚀 Nchan MCP Transport
To use Nchan MCP Transport, install the server SDK with pip install httmcp, run the demo in Docker, and define your tools using Python decorators. Key features of Nchan MCP Transport? Dual Protocol Support: Supports WebSocket and SSE with automatic detection. High Performance Pub/Sub: Built on Nginx + Nchan, handling thousands of concurrent connections. MCP-Compliant Transport: Fully implements Model Context Protocol (JSON-RPC 2.0). OpenAPI Integration: Auto-generate MCP tools from any OpenAPI spec. Tool / Resource System: Register tools and resources using Python decorators. Asynchronous Execution: Background task queue with live progress updates. Dockerized Deployment: Easily deployable with Docker Compose. Use cases of Nchan MCP Transport? Building Claude plugin servers over WebSocket/SSE. Creating real-time LLM agent backends. Connecting Claude to internal APIs via OpenAPI. Serving as a high-performance tool/service bridge for MCP. FAQ from Nchan MCP Transport? What are the requirements for Nchan MCP Transport? Requires Nginx with Nchan module, Python 3.9+, and Docker/Docker Compose. Is it easy to deploy? Yes! It can be easily deployed using Docker Compose.
Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.
Use Cases for this MCP Server
- No use cases specified.
MCP servers like 🚀 Nchan MCP Transport can be used with various AI models including Claude and other language models to extend their capabilities through the Model Context Protocol.
About Model Context Protocol (MCP)
The Model Context Protocol (MCP) is a standardized way for AI agents to communicate with various services and tools. MCP servers like 🚀 Nchan MCP Transport provide specific capabilities that can be accessed through a consistent interface, making it easier to build powerful AI applications with complex workflows.
Browse the MCP Directory to discover more servers and clients that can enhance your AI agents' capabilities.