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.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"nchan-mcp-transport": {
"command": "<see-readme>",
"args": []
}
}
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A high-performance WebSocket/SSE transport layer & gateway for Anthropic's MCP (Model Context Protocol) — powered by Nginx, Nchan, and FastAPI. > For building real-time, scalable AI integrations with Claude and other LLM agents.
No automated test available for this server. Check the GitHub README for setup instructions.
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A high-performance WebSocket/SSE transport layer & gateway for Anthropic's MCP (Model Context Protocol) — powered by Nginx, Nchan, and FastAPI.
For building real-time, scalable AI integrations with Claude and other LLM agents.
Nchan MCP Transport provides a real-time API gateway for MCP clients (like Claude) to talk to your tools and services over:
✅ Ideal for AI developers building Claude plugins, LLM agents, or integrating external APIs into Claude via MCP.
| Feature | Description |
|---|---|
| 🔄 Dual Protocol Support | Seamlessly supports WebSocket and SSE with automatic detection |
| 🚀 High Performance Pub/Sub | Built on Nginx + Nchan, handles 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 | Use Python decorators to register tools and resources |
| 📡 Asynchronous Execution | Background task queue + live progress updates via push notifications |
| 🧱 Dockerized Deployment | Easily spin up with Docker Compose |
MCP lets AI assistants like Claude talk to external tools. But:
FastMCP) may not scale under load✅ Nchan MCP Transport gives you:
pip install httmcp
git clone https://github.com/yourusername/nchan-mcp-transport.git
cd nchan-mcp-transport
docker-compose up -d
@server.tool()
async def search_docs(query: str) -> str:
return f"Searching for {query}..."
openapi_server = await OpenAPIMCP.from_openapi("https://example.com/openapi.json", publish_server="http://nchan:80")
app.include_router(openapi_server.router)
HTTMCP provides a powerful CLI for instant deployment of GPTs Actions to MCP servers:
# Installation
pip install httmcp[cli]
# One-click deployment from GPTs Actions OpenAPI spec
python -m httmcp -f gpt_actions_openapi.json -p http://nchan:80
mcp transport, nchan websocket, sse for anthropic, mcp jsonrpc gateway, `claude plugin