Time-MCP MCP Server: Real-Time Timezone-Aware Date and Time Information

Overview: What is Time-MCP MCP Server?

Time-MCP is an MCP (Model Context Protocol) server designed to provide real-time timezone-aware date and time information, enabling seamless integration with AI applications via a standardized protocol. This server is built using Python and leverages the robust zoneinfo module for comprehensive timezone support. The core functionality includes fetching the current time in any IANA timezone, offering easy integration with Claude Desktop and other MCP clients through MCP.

🔧 Core Features & MCP Capabilities

Time-MCP provides essential features that enable deeper integration between AI applications and real-world data sources:

• Real-Time Timezone-Aware Data: Fetching accurate local times ensures that AI applications can make contextually aware decisions based on time-sensitive data.

• MCP Protocol Support: Seamless communication with MCP clients, including Claude Desktop. This support facilitates the exchange of structured information and commands, enhancing the utility of AI tools.

• Comprehensive Timezone Support: Utilizing Python’s zoneinfo module ensures that every IANA timezone is represented accurately, aiding in a wide range of deployment scenarios.

• Simple JSON Responses: All responses are formatted in ISO 8601 standard, making them easily consumable by client applications.

⚙️ MCP Architecture & Protocol Implementation

The architecture of Time-MCP is designed to be flexible and highly compatible with various AI clients. The core component is the server, which acts as a bridge between the AI application and real-time time data. The protocol implementation ensures security and efficiency in data exchange.

MVP Diagram: MCP Protocol Flow

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

Client Compatibility Matrix

MCP Client	Resources	Tools	Prompts	Status
Claude Desktop	✅	✅	✅	Full Support
Continue	✅	✅	✅	Full Support
Cursor	❌	✅	❌	Tools Only

🚀 Getting Started with Installation

To get Time-MCP up and running, follow these steps:

Step 1: Clone the Repository

git clone https://github.com/yourusername/time-mcp.git
cd time-mcp

Step 2: Set Up Virtual Environment

Use uv for a virtual environment setup.

uv venv
source .venv/bin/activate

Step 3: Install the Package

Install Time-MCP with the following command:

pip install -e .

💡 Key Use Cases in AI Workflows

Time-MCP offers versatile use cases in AI workflows, enhancing real-time data processing and analysis. Below are two scenarios that vividly illustrate its utility.

Scenario 1: Weather Forecasting

An AI-driven weather forecasting tool can leverage Time-MCP to ensure accurate local time for different regions based on IANA timezone identifiers. This integration allows the tool to provide precise weather reports that account for differences in daylight saving times and other local factors, improving user experience and reliability.

• Technical Implementation: The server can be queried with specific timestamps or time zones to retrieve relevant data for forecast calculations.

Scenario 2: Financial Trading

Real-time financial trading applications require up-to-date market information across multiple geographical locations. Time-MCP provides the necessary timezone-aware updates so that trades are executed correctly based on local business hours and other temporal conditions.

• Technical Implementation: Clients can request time zones of different stock exchanges globally, ensuring compliance with trading regulations and reducing latency in transaction timing.

🔌 Integration with MCP Clients

Time-MCP supports integration with major MCP clients through a standardized protocol. The key components are as follows:

• Server Connection: The server establishes a connection with the client via the MCP protocol.

• Tool Execution: Once connected, tools like get_current_time can be executed to fetch real-time timezone data.

📊 Performance & Compatibility Matrix

Feature	Performance	Compatibility
Response Time	<100ms for tz queries	All IANA timezones supported
API Rate Limiting	100 requests per minute	Yes
Client Support	Claude Desktop, Continue, Cursor (limited tool support)	Partial

🛠️ Advanced Configuration & Security

Advanced users can customize and secure the Time-MCP server configuration.

MCP Server Config Sample

{
  "mcpServers": {
    "[server-name]": {
      "command": "npx",
      "args": ["-y", "@modelcontextprotocol/server-[name]"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

Security Considerations

• Authentication: Implement API keys for client validation.

• Data Encryption: Ensure data transmitted over the network is encrypted using TLS.

❓ Frequently Asked Questions (FAQ)

1. Can Time-MCP be used with other AI clients?

   • Yes, Time-MCP supports integration with other MCP clients like Claude Desktop and Continue through their respective tools.

2. How do I test the server for performance?

   • Use load testing tools to simulate high request volumes and measure response times.

3. Can I customize the timezone parameters in queries?

   • Yes, you can specify any valid IANA timezone identifier as a parameter.

4. Is Time-MCP compatible with specific versions of Python?

   • Time-MCP requires Python 3.10 or later due to dependencies on newer language features and libraries.

5. How do I set up environment variables for secure operations?

   • Use env in the server configuration sample to define necessary key-value pairs securely.

👨‍💻 Development & Contribution Guidelines

Contributions are welcome! To contribute, please follow these steps:

1. Fork the repository.
2. Clone and set up your local environment.
3. Make changes and submit a pull request.

Community Resources

• Repository: https://github.com/yourusername/time-mcp
• Issues & Discussions: Join the community to report issues or discuss features on GitHub.

🌐 MCP Ecosystem & Resources

Stay updated with the latest developments in the MCP ecosystem:

• MCP Documentation: Detailed guides and specifications for developers.
• Community Forums: Engage with other developers and share knowledge about implementing MCP protocols.

By leveraging Time-MCP, AI applications can enhance their capabilities to handle time-sensitive tasks more effectively. This documentation provides a comprehensive guide to installation, usage, and development, ensuring smooth integration into your AI workflows.