MCP-Template
a Python starter project for building an MCP (Model Context Protocol) server. It includes a server, a client pool to manage multiple connections safely, and a Jupyter notebook demonstrating how to use the tools and communicate with the AI. The project is structured to make it easy to add your own tools, prompts, and workflows. To get started, clone the repository, install dependencies, run the server, and use the notebook to test and interact with your MCP setup.
Prerequisites:
Create a virtual environment (conda or python) and activate it
# Python Virtual Environment (Create) python -m venv .venv # Activating (Windows) .\.venv\Scripts\activate # Activating (Linux/MacOS) source .venv/bin/activate# Conda Virtual Environment (Create) conda create -n myenv python=3.11 # Activating conda activate myenvpip install the requirements (in the environment)
pip install -r requirements.txtMake sure you have an Azure client (or OpenAI; you may need to update the code if new fields are required). Create a
.envfile in the project root directory with the following fields:AZURE_API_KEY="Your API Key" ENDPOINT="Your Endpoint" VERSION="Your OpenAI Version" MODEL="Your Azure OpenAI Model"
Sources
Official MCP Documentation: https://modelcontextprotocol.io/docs/getting-started/intro
Official MCP Python-SDK: https://github.com/modelcontextprotocol/python-sdk
This server cannot be installed
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
A Python starter template for building MCP servers with client connection management and Jupyter notebook integration. Provides a structured foundation for adding custom tools, prompts, and workflows to create AI-powered applications.