mcp_server_client_tutorial_using_python

The Model Context Protocol (MCP) is designed to facilitate communication between language models and tool providers, enabling powerful AI-based applications. This guide walks you through creating both an MCP server and a client with a graphical user interface using Python. By the end of this tutorial, you'll have a functional MCP system with both server and client components that can interact seamlessly. The server is implemented to handle tool calls, such as a simple addition operation, while the client connects to the server, calls the tools, and displays results. The client UI is built using Tkinter, providing a user-friendly interface for interaction. The guide also covers asynchronous programming considerations and provides scripts for setting up and running the server and client.

Features

• Comprehensive guide for building MCP server and client
• Includes UI development using Tkinter
• Covers asynchronous programming in Python
• Provides scripts for server and client setup
• Demonstrates tool call handling and result display

Usage with Different Platforms

mcp_server_setup

bash
cd "your_desired_directory"
uvx create-mcp-server
cd server-project-name
uv sync --dev --all-extras

mcp_server_run

bash
python -m server_project_name.server

mcp_client_setup

bash
uv init mcp-client
cd mcp-client
uv venv
# Activate the virtual environment
# On Windows:
.venv\Scripts\activate
# On macOS/Linux:
source .venv/bin/activate

# Install required packages
uv add mcp anthropic python-dotenv

mcp_client_run

bash
cd mcp-client
python client_ui.py