Reference Servers · MODEL CONTEXT PROTOCOL
MorvanZhou customized mcp
a demo of customized mcp
WHAT IT CONNECTS
What MorvanZhou customized mcp gives an AI Agent
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SECURITY
An MCP listing is not a security review
An MCP server may receive model context, credentials, local files, or permission to call external systems. Review its code, requested environment variables, network behavior, package provenance, and maintenance status before connecting it to an agent.
README
Repository documentation
This project leverages the mcp library with CLI support and integrates with OpenAI's API.
Make sure to install the required dependencies before running the project:
pip install -r requirements.txt-
Configure your OpenAI API key as an environment variable:
export OPENAI_API_KEY="your-api-key"
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Start the MCP server:
python server.py
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Use the client to interact with the server:
python client.py
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Alternatively, use the orchestrator to query the LLM and tools:
python main.py
Run the client and call the get_weather tool:
python client.pyExample interaction:
You: List tools
Assistant: {
"tools": [
{
"name": "get_weather",
"description": "Get weather for a city",
"parameters": {
"city": {
"type": "string",
"description": "Name of the city"
}
}
}
]
}
You: Call get_weather with {"city": "Beijing"}
Assistant: 北京的天气是晴天
openai==1.70.0mcp[cli]==1.6.0
This project is licensed under the MIT License.
COMMUNITY