Robust timezone-aware MCP Time Server with IANA support, cross-platform, high performance, and comprehensive testing
The MCP Time Server is an essential component in the Model Context Protocol (MCP) ecosystem, providing timezone-aware time synchronization to a variety of AI applications through a standardized protocol. This server ensures that all connected entities maintain accurate and consistent temporal integrity, crucial for operations that depend on reliable timestamps.
The MCP Time Server boasts several key features designed to enhance the integration process with MCP clients:
tzdata: Facilitating seamless operation on multiple operating systems without requiring external dependencies, making maintenance easier and more reliable.The architecture of the MCP Time Server is meticulously designed to align with the Model Context Protocol. It leverages a combination of internal time management and external API interactions, ensuring synchronous data transfer through well-defined endpoints. The protocol implementation includes methods for configuring timezone settings, error logging, and performance metrics reporting.
To deploy or install the MCP Time Server, simply execute the following command:
pip install mcp-time-server
For development purposes, use this additional setup step:
# Install development dependencies
pip install -e ".[dev]"
# Run tests
pytest
Imagine a scheduler app that needs to remind users about meetings or appointments. By integrating with the MCP Time Server, it can ensure reminders are sent at the precise moment despite varying location-specific time zones.
# Example of setting up timezone-aware scheduling in Python
from mcp_time_server import TimeServerClient
client = TimeServerClient()
meeting_time = client.get_timezone_aware_time("America/New_York")
reminder_service.set_reminder(meeting_time, "Weekly Status Meeting")
In an AI workflow where log data needs to be timestamped accurately based on local time zones, the MCP Time Server will ensure that every event is recorded with the correct time.
# Example of logging timezone-aware events in Python
from mcp_time_server import TimeServerClient
client = TimeServerClient()
log_entry = f"Data point captured at {client.get_timezone_aware_time('Europe/London')}"
logger.log(log_entry)
The following table outlines the current compatibility of the MCP Time Server with various MCP clients:
| MCP Client | Resources | Tools | Prompts | Status |
|---|---|---|---|---|
| Claude Desktop | ✅ | ✅ | ✅ | Full Support |
| Continue | ✅ | ✅ | ✅ | Full Support |
| Cursor | ❌ | ✅ | ❌ | Tools Only |
The performance and compatibility of the MCP Time Server are robust, catering to a wide range of use cases. The server is tested against known time zones to ensure accuracy and reliable support.
graph TD
A[AI Application] -->|MCP Client| B[MCP Protocol]
B --> C[MCP Server]
C --> D[Data Source/Tool]
style A fill:#e1f5fe
style C fill:#f3e5f5
style D fill:#e8f5e8
graph LR
subgraph MCP Server Components
TimeServer -->|Fetch Zone Information| TZDatabase
TimeServer <--|Generate Timestamps| ApplicationEvents
TimeServer -->|Provide Timestamped Events| ApplicationClients
end
Customizing the MCP Time Server can be done through the following configuration snippet:
{
"mcpServers": {
"[server-name]": {
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-[name]"],
"env": {
"API_KEY": "your-api-key"
}
}
}
}
Ensure that the API_KEY is securely managed and updated as necessary to protect against unauthorized access.
A: The server includes a bundled tzdata package, ensuring it works seamlessly on any platform without requiring external dependencies.
A: Currently, Cursor has limited support as indicated in the client matrix. Further testing is required for full integration.
A: Yes, user-defined error handlers can be implemented by extending the server's error management methods.
A: It updates automatically based on periodic checks and manual deployment of new versions that include latest timezone data.
A: The server supports all IANA-defined time zones, providing extensive coverage for diverse applications.
Contributions to the MCP Time Server are welcomed. Interested developers should follow these steps:
Fork the repository on GitHub.
Clone your fork and install dependencies:
git clone https://github.com/your-username/mcp-time-server.git
cd mcp-time-server
pip install -e ".[dev]"
Run the test suite to ensure new code integrates smoothly:
pytest
Submit a pull request with clear documentation for any contributions.
Explore more about the Model Context Protocol and its applications through these resources:
By leveraging the MCP Time Server, AI application providers can ensure seamless integration and operation across various time zones, enhancing user experience and operational efficiency.
RuinedFooocus is a local AI image generator and chatbot image server for seamless creative control
Learn to set up MCP Airflow Database server for efficient database interactions and querying airflow data
Simplify MySQL queries with Java-based MysqlMcpServer for easy standard input-output communication
Explore CoRT MCP server for advanced self-arguing AI with multi-LLM inference and enhanced evaluation methods
Build stunning one-page websites track engagement create QR codes monetize content easily with Acalytica
Access NASA APIs for space data, images, asteroids, weather, and exoplanets via MCP integration