MCP Client-Server Python - MCP Server

MCP Client-Server Python Example

This project demonstrates a simple client-server MCP.

What is MCP (Model Context Protocol)?

MCP is an open protocol introduced by Anthropic to enable large language models (LLMs) to interact with external tools, APIs, and resources in a standardized, extensible way.
It facilitates secure, multi-channel communication between AI models and external systems, supporting advanced agentic workflows and tool use.

🔗 Anthropic's announcement
🔗 MCP documentation

Features

MCP Server: Exposes tools (e.g., addition) and resources (e.g., greetings) via SSE.
MCP Client: Connects to the server, lists available tools, and interacts using OpenAI's chat completions.
OpenAI Integration: Uses OpenAI's GPT models to process user queries and call server tools as needed.

Requirements

Python 3.12+
MCP Python SDK
OpenAI Python SDK
Uvicorn (for running the server)
python-dotenv (for loading environment variables)
uv (fast Python package installer and resolver)

Project Structure

.
├── client.py      # MCP client implementation
├── server.py      # MCP server implementation
├── pyproject.toml # Project metadata and dependencies
├── .env           # Environment variables (not committed)
└── README.md      # This file

Install dependencies with uv:

uv sync

(This will install all dependencies as specified in uv.lock.)

Setup

Environment Variables

Create a .env file in the project directory:

OPENAI_API_KEY=your-openai-api-key
MCP_SSE_URL=http://localhost:8080/sse

Start the Server
```
uv run server.py --host 0.0.0.0 --port 8080
```
The server exposes tools and resources via SSE at /sse.
Run the Client

In another terminal:
```
uv run client.py
```
The client will connect to the server, list available tools, and start an interactive chat loop.

Usage

Type your queries in the client prompt.
The client will use OpenAI to process your query and call server tools if needed.
Type quit to exit the client.