mcpField
M
MCP Time Server

MCP Time Server

Local
github.com/chrishayukProductivity4Updated 74w ago

About MCP Time Server

MCP Time Server is a Python service for retrieving local time and converting times across IANA time zones. It is intended for MCP clients that need validated time utilities, with configurable settings and an asynchronous server architecture.

Key features

  1. 01Get current time by timezone
  2. 02Convert times between zones
  3. 03Validate inputs with Pydantic
  4. 04Configure through environment and files

Use cases

  1. 01Check the current time in a region
  2. 02Convert a meeting time across zones

MCP support

Exposes tools to MCP clients for retrieving current time in an IANA timezone and converting a specified time between timezones.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

No install method listed yet

We haven’t collected a package or remote endpoint for this server. Follow the instructions in the project README.

Repository

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

MCP Time Server

Overview

The MCP Time Server is a sophisticated Python-based microservice designed to provide advanced time-related utilities across different timezones. It offers robust functionality for retrieving current times and converting times between various global timezones.

Project Details

  • Version: 0.1.1
  • Python Compatibility: Python 3.11+

Features

  • Current Time Retrieval: Get the current time for any IANA timezone
  • Time Zone Conversion: Convert times between different time zones
  • Comprehensive Validation: Robust input validation using Pydantic models
  • Async Server Architecture: Built with asyncio for efficient performance
  • Flexible Configuration: Configurable through environment variables and config files

Dependencies

Core dependencies:

  • mcp (>=1.6.0)
  • pydantic (>=2.11.2)
  • PyYAML (>=6.0.2)
  • pyz (>=0.4.3)

Development dependencies:

  • pytest (>=8.3.5)

Installation

Prerequisites
  • Python 3.11 or higher
  • pip
  • (Optional) Virtual environment recommended
Install from PyPI
pip install chuk-mcp-artifact-server
Install from Source
  1. Clone the repository:
git clone <repository-url>
cd chuk-mcp-artifact-server
  1. Create a virtual environment:
python -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`
  1. Install the package:
pip install .  # Installs the package in editable mode
Development Installation

To set up for development:

pip install .[dev]  # Installs package with development dependencies

Running the Server

Command-Line Interface
chuk-mcp-artifact-server
Programmatic Usage
from chuk_mcp_artifact_server.main import main

if __name__ == "__main__":
    main()

Environment Variables

  • NO_BOOTSTRAP: Set to disable component bootstrapping
  • Other configuration options can be set in the configuration files

Available Tools

1. Get Current Time

Input:

  • timezone: IANA timezone name (e.g., 'America/New_York')

Example:

get_current_time('Europe/London')

Returns:

  • Current time in the specified timezone
  • Timezone details
  • Daylight Saving Time (DST) status
2. Convert Time

Input:

  • source_timezone: Source timezone (IANA format)
  • time: Time in HH:MM (24-hour) format
  • target_timezone: Target timezone (IANA format)

Example:

convert_time('America/New_York', '14:30', 'Europe/Paris')

Returns:

  • Source time details
  • Target time details
  • Time difference between zones

Development

Code Formatting
  • Black is used for code formatting
  • isort is used for import sorting
  • Line length is set to 88 characters
Running Tests
pytest

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/AmazingFeature)
  3. Ensure code passes formatting and testing
  4. Commit your changes (git commit -m 'Add some AmazingFeature')
  5. Push to the branch (git push origin feature/AmazingFeature)
  6. Open a Pull Request

License

MIT License

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.