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MCP-123

by Tylersuard
GitHub
Python
23
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🚀 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.

🤝 Credits

  • Built with FastMCP
  • Inspired by the Model Context Protocol (MCP)

📬 Feedback & Contributions

Pull requests and issues are welcome, but only if they are in ALL-CAPS.

This server cannot be installed

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security - not tested
F
license - not found
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quality - not tested

How are these scores calculated?

hybrid server

The server is able to function both locally and remotely, depending on the configuration or use case.

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.

  1. 🖥️ Quickstart
    1. 1. Install Requirements
    2. 2. Create Your Tools
    3. 3. Start the MCP Server (2 lines)
    4. 4. Set up the MCP Client (2 lines)
    5. 5. Use the MCP Client
    6. 6. Close the MCP Client when you are done
  2. 🚀 Features
    1. 📝 How It Works
      1. 🛠️ Example Output
        1. 🔑 Requirements
          1. 📢 Why MCP123?
            1. 🤝 Credits
              1. 📬 Feedback & Contributions

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