本项目实现了最小的mcp项目，方便理解整个MCP系统的运行，
项目使用了deepseek的api_key,请在.env文件中添加你的api_key
如果使用其他LLM服务，请在env文件中添加相应的API_KEY，请选择支持MCP服务的LLM服务
├── .env
├── .gitignore
├── client/client.py
├── client/server.json
├── server/tasklist.py
├── pyproject.toml
|── tasks.csv
|── README.md
uv venv
# Activate virtual environment
# On Windows:
.venv\Scripts\activate
# On Unix or MacOS:
source .venv/bin/activate## 使用openai格式来访问
uv add mcp openai python-dotenvtouch .envecho "OPENAI_API_KEY=your_api_key" >> .env
echo "OPENAI_BASE_URL="https://api.deepseek.com/v1"" >> .env
echo "OPENAI_MODEL="deepseek-chat" >> .env{
"servers": [
{
"command": "uv",
"args": ["run","../server/tasklist.py"],
"env": null
},
{
"command": "uv",
"args": ["run","../server/weather.py"],
"env": null
},
{
"command": "npx",
"args": ["-y","../server/stock.js"],
"env": null
}
]
}cd client
uv run client.py server.json然后输入用户query即可