MCP Server Demo
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@MCP Server Demochat with me about artificial intelligence"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
MCP Server
基于WebSocket的MCP(Model Control Protocol)服务器,用于处理模型请求并提供响应。
项目结构
MCPServerDemo/
├── src/ # 源代码目录
│ └── mcp/ # MCP实现
│ ├── handlers/ # 请求处理器
│ ├── models/ # 数据模型
│ ├── protocol/ # 协议定义
│ └── server/ # 服务器实现
├── client/ # 客户端示例
│ └── index.html # 测试用HTML客户端
├── .env # 环境变量配置(需要从.env.example创建)
├── .env.example # 环境变量示例
├── main.py # 应用程序入口点
└── README.md # 项目说明Related MCP server: FastAPI MCP Server
安装
本项目使用uv进行依赖管理。
# 安装依赖
uv pip install fastapi uvicorn pydantic pydantic-settings配置
复制环境变量示例文件并进行配置:
cp .env.example .env编辑
.env文件,设置您的配置。
运行
# 启动服务器
python main.py服务器将在http://localhost:8000上运行,WebSocket端点为ws://localhost:8000/ws。
测试客户端
打开client/index.html文件在浏览器中测试MCP服务器。
MCP协议
MCP协议是一个基于WebSocket的协议,用于控制和管理AI模型。
请求格式
{
"id": "请求ID",
"type": "request",
"action": "动作名称",
"messages": [
{
"role": "user",
"content": "消息内容"
}
],
"parameters": {
"参数名": "参数值"
}
}响应格式
{
"id": "请求ID",
"type": "response",
"action": "动作名称",
"messages": [
{
"role": "assistant",
"content": "响应内容"
}
],
"metadata": {
"元数据名": "元数据值"
}
}错误格式
{
"id": "请求ID",
"type": "error",
"action": "动作名称",
"error": "错误信息",
"details": {
"详情名": "详情值"
}
}事件格式
{
"id": "事件ID",
"type": "event",
"event": "事件名称",
"data": {
"数据名": "数据值"
}
}支持的动作
chat: 聊天请求completion: 文本完成请求
扩展
您可以通过以下方式扩展MCP服务器:
创建新的处理器在
src/mcp/handlers/目录在
main.py中注册新的处理器自定义协议实现在
src/mcp/protocol/目录
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