MCP 服务器

MCP-123

A minimal Python package for easily setting up and running MCP servers and clients, allowing functions to be automatically exposed as tools that LLMs can use with just 2 lines of code.

README

<h1 align="center"> MCP-123 <br> <sub>The easiest way to run an MCP server & client (2 lines each)</sub> </h1>

🚀 Features

Ultra-minimal setup: Start a server or client in 2 lines.
Easy tool creation: Write normal functions in your tools.py file—no decorators or special wrappers needed—and they get included as tools that your MCP server can use automatically.
OpenAI integration: The client uses your OpenAI API key to answer questions, calling tools as needed.

🖥️ Quickstart

1. Install Requirements


pip install -r requirements.txt

2. Create Your Tools

Define your functions in tools.py. No decorators needed, they are automatically added to your MCP server as tools. For example:


def add(a: int, b: int) -> int:

    """Add two numbers."""

    return a + b

3. Start the MCP Server (2 lines)


from mcp123 import server

server.run_server("tools.py", port=9999)

4. Set up the MCP Client (2 lines)


from mcp123.client import McpClient

client = McpClient("http://localhost:9999", "sk-...your OpenAI key...")

5. Use the MCP Client


answer = client.ask("Add 15 and 14.")

print("Answer:", answer)

6. Close the MCP Client when you are done


client.close()

🚀 Features

Ultra-minimal setup: Start a server or client in 2 lines.
Easy tool creation: Write normal functions in your tools.py file—no decorators or special wrappers needed—and they get included as tools that your MCP server can use automatically.
OpenAI integration: The client uses your OpenAI API key to answer questions, calling tools as needed.

📝 How It Works

Server: Loads all top-level functions from tools.py and exposes them as MCP tools via HTTP.
Client: Discovers available tools, sends prompts to OpenAI, and automatically calls tools if needed.

🛠️ Example Output

When you run the client, you’ll see:


Tools discovered:

 [ ...list of tools... ]



Answer: 29

🔑 Requirements

Python 3.11+
OpenAI API key (for the client)

📢 Why MCP123?

Zero boilerplate: No need to write schemas or wrappers—just write functions.
LLM-native: Designed for seamless LLM tool use.
Extensible: Add more tools by simply adding functions.