Python project template

what is mcp-python-server? The mcp-python-server is a template repository designed for Python projects, providing essential development tools and configurations to streamline the development process. how to use mcp-python-server? To use this template, clone the repository, set up a development environment using either a devcontainer or a virtual environment, and start adding your code and tests. key features of mcp-python-server? Pre-configured development tools including ruff for error checking and black for code formatting. Integration with pytest for testing and coverage measurement. Automated checks and tests using GitHub Actions on pull requests and merges. use cases of mcp-python-server? Setting up a new Python project quickly with best practices. Ensuring code quality through automated checks and formatting. Facilitating collaboration with integrated testing and CI/CD workflows. FAQ from mcp-python-server? What Python version is supported? This template is set up for Python 3.11, but can be adjusted as needed. How do I run tests? You can run tests using the command python3 -m pytest after setting up your environment. Is there documentation available? Yes, detailed instructions are provided in the README file of the repository.

As an MCP (Model Context Protocol) server, Python project template enables AI agents to communicate effectively through standardized interfaces. The Model Context Protocol simplifies integration between different AI models and agent systems.

To use this template, clone the repository, set up a development environment using either a devcontainer or a virtual environment, and start adding your code and tests. key features of mcp-python-server? Pre-configured development tools including ruff for error checking and black for code formatting. Integration with pytest for testing and coverage measurement. Automated checks and tests using GitHub Actions on pull requests and merges. use cases of mcp-python-server? Setting up a new Python project quickly with best practices. Ensuring code quality through automated checks and formatting. Facilitating collaboration with integrated testing and CI/CD workflows. FAQ from mcp-python-server? What Python version is supported? This template is set up for Python 3.11, but can be adjusted as needed. How do I run tests? You can run tests using the command python3 -m pytest after setting up your environment. Is there documentation available? Yes, detailed instructions are provided in the README file of the repository.

Learn how to integrate this MCP server with your AI agents and leverage the Model Context Protocol for enhanced capabilities.