What are the runtime requirements?
Node.js version 20 or higher and npm are required.
@LiusDev
基本信息
This repository demonstrates a NestJS implementation of the Model Context Protocol (MCP) with a microservice architecture.
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"nestjs-mcp-server": {
"type": "http",
"url": "http://localhost:3000/sse"
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
点击上方按钮,直接连接服务器端点实时获取工具列表。
This repository demonstrates a NestJS implementation of the Model Context Protocol (MCP) with a microservice architecture. It comprises two services: an MCP server that provides time context functions for LLMs, and an MCP backend client that uses LangChain.js and the MCP client SDK to connect to the server. It is intended for developers building context-aware LLM applications with NestJS.
Install Node.js 20+, clone the repo, run npm install, copy .env.example to .env and add your OpenAI API key. Start both services using npm run start:dev mcp-server and npm run start:dev mcp-backend. Send a POST request to http://localhost:3001 with a JSON body containing a message field (e.g., "What time is it in Viet Nam?") to receive the current time.
Node.js version 20 or higher and npm are required.
Use `npm run start:dev mcp-server` for the MCP server and `npm run start:dev mcp-backend` for the backend.
The MCP server uses Server-Sent Events (SSE) transport, with configuration options for reconnection.
An OpenAI API key must be provided in the `.env` file under `OPENAI_API_KEY`.
Yes. You can configure additional servers in `McpClientModule.register` with unique keys and ports. The client fetches tools from all configured servers.

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