python -template
A template repository for Python MCP Servers
claude mcp add --transport stdio fidelusaleksander-python-mcp-server-template python server/main.py
How to use
This Python MCP server template provides a minimal MCP server built with the Python SDK. It exposes a ready-to-run server skeleton that you can customize to implement your own Model Context Protocol (MCP) endpoints. You can run the server directly in development or use the MCP tooling to test and inspect interactions with the MCP Inspector. To develop locally, you can start the server with python server/main.py and then connect tooling or clients to the configured MCP endpoint to exchange context models, policies, and other MCP artifacts.
How to install
Prerequisites:
- Python 3.13+ installed
- uv package manager installed (recommended for environment setup and virtual environments)
Steps:
-
Obtain the template (clone or download the repository). Example: git clone https://github.com/fidelusaleksander-python-mcp-server-template.git cd fidelusaleksander-python-mcp-server-template
-
Set up the Python environment using uv (as described in the template).
- Install dependencies and create/activate the virtual environment: uv sync source .venv/bin/activate
-
Install additional dependencies if needed (optional):
- If a requirements file exists, install with: pip install -r requirements.txt
-
Run the server:
- Development/run directly: python server/main.py
- If you prefer using MCP development tooling, you can run tests or inspect with the MCP Inspector as described in the template documentation.
Additional notes
Tips and common questions:
- This template is designed for quick-starting an MCP server in Python. Customize server/main.py to implement your MCP endpoints and logic.
- Use uv sync to manage the virtual environment and dependencies; activate the environment before running the server.
- Development tooling like the MCP Inspector can help you test interactions with your MCP server. You can launch the inspector and point it at your local MCP endpoint.
- If you upgrade Python, re-create the virtual environment to ensure compatibility with dependencies.
- Ensure your server port and endpoint configuration match what your clients or inspector expect.
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