If you've ever wondered what is MCP or how to simplify communication with MCP servers, this guide will show you exactly how. The Model Context Protocol (MCP) allows developers to build powerful agent-based applications by connecting any large language model (LLM) directly to a server. With this newly introduced MCP client library, you no longer need complex setups or dedicated clients like Claude, WinServe, or Desktop. It’s simple, effective, and works with popular environments like Cursor.

GitHub Repository:
https://github.com/pietrozullo/mcp-use

# Check the installed Python version
python --version

# Create a virtual environment named 'venv' using Python 3
python3 -m venv venv

# Activate the virtual environment on macOS/Linux
source venv/bin/activate

# Activate the virtual environment on Windows
.\venv\Scripts\activate


In this MCP tutorial, you'll learn how to set up your MCP server using Python, create virtual environments, install required packages like LangChain for OpenAI or Anthropic, and configure your .env file with your API key. Whether you're integrating with OpenAI, Claude, or Llama, this framework supports a variety of backends and makes creating custom agents effortless.

Once installed, you’ll build your own MCP agent, define LLMs, and run tasks using the MCP server setup. The code executes a prompt and retrieves results filtered by specific conditions, like Airbnb listings with a pool. This shows how easily the MCP can be used to build modular applications.

One of the standout features is multi-server support — you can define multiple MCP servers in a single file and dynamically assign tasks based on your agent’s preferences. The UseServiceManager flag enables intelligent server selection, making MCP server creation streamlined and efficient.

Need help? The Cursor editor allows you to load the GitHub documentation directly for smarter coding assistance. This works seamlessly with tools like ChatGPT or Claude, providing a comprehensive AI MCP coding experience. Curious about Claude MCP or how to use MCP in n8n workflows? The library has you covered.

Explore the repo, try the examples, and start building with this flexible, open-source GitHub MCP solution. Whether you're new to the protocol or just looking to understand how MCP explained fits into the future of AI, this is the perfect starting point.