chuk -time

The MCP Time Server provides two main tools for working with timezones: getting the current time for a specific IANA timezone and converting a time between two time zones. It validates inputs with Pydantic, handles asynchronous operations for efficiency, and can be configured via environment variables or configuration files. To use the server locally, start it using the Python module entry point shown in the installation guide, then interact with the CLI or, if you’re integrating programmatically, import and call the provided functions for getting the current time or performing conversions. The tools are designed to be simple to use in scripts or within other MCP workflows, returning structured details about time, timezone information, and DST status.

Prerequisites:\n- Python 3.11 or higher\n- pip\n- Optional: virtual environment recommended\n\nInstall from PyPI:\nbash\npip install chuk-mcp-artifact-server\n\n\nInstall from Source:\n1. Clone the repository:\nbash\ngit clone <repository-url>\ncd chuk-mcp-artifact-server\n\n2. Create a virtual environment:\nbash\npython -m venv venv\nsource venv/bin/activate # On Windows, use `venv\Scripts\activate`\n\n3. Install the package:\nbash\npip install . # Installs the package in editable mode\n\n\nDevelopment Installation:\nbash\npip install .[dev] # Installs package with development dependencies\n\n\nRunning the server:\nbash\nchuk-mcp-artifact-server # From CLI (if installed as an entry point)\n\n\nProgrammatic usage example in code:\npython\nfrom chuk_mcp_artifact_server.main import main\n\nif __name__ == "__main__":\n main()\n

Environment variables and configuration options can customize behavior. Common variables include NO_BOOTSTRAP to disable component bootstrapping. Configuration may also be managed via config files as described by the project. If you encounter import errors, ensure the package is installed in the same Python environment you’re running, especially inside virtual environments. For unit testing, pytest is listed as a development dependency; you can run tests with pytest. The server is built with asyncio for asynchronous performance, so integration with other async components can be straightforward.