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MCP Hello World Example

by wubbyweb

AI/IntegrationOpenAIFlaskFunction CallingAPI

This project demonstrates a simple implementation of the Model Context Protocol (MCP) using a Flask server and OpenAI integration. It showcases how to create an MCP server with a number addition function and a client that uses it through OpenAI's function calling.

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MCP Hello World Example

This project demonstrates a simple implementation of the Model Context Protocol (MCP) using a Flask server and OpenAI integration. It showcases how to create an MCP server that provides a number addition function and a client that can use this function through OpenAI's function calling capabilities.

Components

Server (server.py)

  • A Flask-based MCP server that implements:
    • A simple addition function (add_numbers)
    • MCP protocol endpoints for function listing and execution
    • JSON schema definition for the addition function
    • Runs on http://localhost:8080

Client (client.py)

  • Integrates with OpenAI's API and the MCP server
  • Demonstrates:
    • Fetching available functions from the MCP server
    • Converting MCP functions to OpenAI function specifications
    • Making function calls through OpenAI's chat completions
    • Processing and displaying results

Prerequisites

  • Python 3.x
  • OpenAI API key

Installation

  1. Clone the repository
  2. Install dependencies:
pip install -r requirements.txt

Configuration

  1. Set your OpenAI API key:
export OPENAI_API_KEY="your-api-key-here"

Usage

  1. Start the MCP server:
python server.py
  1. In a separate terminal, run the client:
python client.py

The client will:

  1. Connect to the MCP server
  2. Fetch available functions
  3. Start a conversation with OpenAI's model
  4. Demonstrate function calling by adding two numbers (42 and 17)
  5. Display the results

Project Structure

.
├── README.md           # Project documentation
├── requirements.txt    # Python dependencies
├── server.py          # MCP server implementation
└── client.py          # OpenAI client implementation

Dependencies

  • python-dotenv: Environment variable management
  • openai: OpenAI API client
  • flask: Web server framework
  • requests: HTTP client library

Example Output

When running the client, you'll see:

  1. Available MCP functions listing
  2. Model's decision to use the addition function
  3. Function execution results
  4. Final response from the model

Contributing

Feel free to submit issues and enhancement requests!