Kukapay MCP Server: Real-Time Geolocation and Time Information

Overview: What is Kukapay MCP Server?

The Kukapay MCP Server is designed to provide real-time geolocation and current time information to AI applications interfacing through Model Context Protocol (MCP). This server acts as a bridge between AI systems like Claude Desktop, Continue, and Cursor, and external services that offer location and time data. By doing so, it enhances the context-aware capabilities of these AI applications, enabling them to deliver more personalized and accurate information to users.

🔧 Core Features & MCP Capabilities

The Kukapay MCP Server leverages the power of MCP by providing a standardized API for accessing geolocation and current time data. Key features include:

1. Real-Time Data Retrieval: The server uses up-to-date APIs from trusted sources like IP address geolocation services and NTP servers to fetch current time and location information.
2. MCP Protocol Compatibility: Fully compatible with MCP clients such as Claude Desktop, Continue, and Cursor, allowing seamless integration without the need for custom code adjustments.
3. Versatile Data Sources: Supports multiple data providers, ensuring reliability and accuracy of geolocation and time services.
4. Efficient Response Time: Optimized to provide quick responses to queries, reducing latency and enhancing user experience.

⚙️ MCP Architecture & Protocol Implementation

The architecture of the Kukapay MCP Server is designed to seamlessly integrate with existing AI systems via MCP. The protocol implementation involves several key components:

1. MCP Client Integration: The server acts as a resource server in the MCP client stack, responding to commands and queries from the client.
2. Data Retrieval Layer: Utilizes external APIs for fetching geolocation and time data, ensuring real-time accuracy.
3. Response Handling: Processes incoming requests, retrieves relevant information, and formats responses according to MCP standards.

Mermaid Diagram 1: MCP Protocol Flow

graph TD
    A[AI Application] -->|MCP Client| B[MCP Protocol]
    B --> C[MCP Server]
    C --> D[Geolocation API/Time Service]
    style A fill:#e1f5fe
    style C fill:#f3e5f5
    style D fill:#e8f5e8

Mermaid Diagram 2: Data Architecture

graph TD
    A[Database] --> B[Geolocation API]
    A --> C[Time Service]
    D[MCP Server] -->|Request| E[Response Handling Layer]
    E --> F[API Response]
    style A fill:#e8f5e8
    style B fill:#e1f5fe
    style C fill:#e1f5fe
    style D fill:#f3e5f5
    style E fill:#f4cccc

🚀 Getting Started with Installation

To set up the Kukapay MCP Server, follow these steps:

1. Clone the Repository:

   git clone https://github.com/kukapay/mcp-server.git
   cd mcp-server
   

2. Install Dependencies:

   npm install
   

3. Configure Environment Variables: Update .env with your API keys.
4. Run the Server:

   npm start
   

💡 Key Use Cases in AI Workflows

1. Weather Forecasting: By integrating geolocation and time data, an AI application can provide precise weather forecasts tailored to a user's location at any given moment.
2. Personalized Notifications: An AI chatbot can send timely notifications based on local times and events, enhancing the user experience.

🔌 Integration with MCP Clients

The Kukapay MCP Server supports full compatibility with MCP clients:

• Claude Desktop: Fully supported for both data retrieval and prompt handling.
• Continue: Supports real-time geolocation and time queries effectively.
• Cursor: Primarily for data retrieval, Cursor can leverage this server without custom coding.

📊 Performance & Compatibility Matrix

MCP Client	Resources	Tools	Prompts
Claude Desktop	✅	✅	✅
Continue	✅	✅	✅
Cursor	❌	✅	❌

🛠️ Advanced Configuration & Security

To fine-tune the Kukapay MCP Server, modify configuration files and secure API keys. Below is a sample configuration:

{
  "mcpServers": {
    "kukapay": {
      "command": "node",
      "args": ["server.js"],
      "env": {
        "API_KEY_LYRASOFT": "<lyrasoft-api-key>",
        "NTP_SERVER": "pool.ntp.org"
      }
    }
  }
}

❓ Frequently Asked Questions (FAQ)

1. Q: How does the Kukapay MCP Server handle privacy? A: The server complies with data privacy regulations, ensuring that user location and time data are securely handled.

2. Q: Can I customize which geolocation APIs the server uses? A: Yes, you can modify the configuration to use different geolocation services as needed.

3. Q: What if multiple requests come in simultaneously? A: The server is designed to handle concurrent requests efficiently without performance degradation.

4. Q: Can I integrate this with my existing MCP infrastructure? A: Absolutely, the Kukapay MCP Server can be easily integrated into any existing MCP ecosystem.

5. Q: Is there support for historical geolocation data retrieval? A: Currently, only real-time data is supported. Future updates may include historical data services.

👨‍💻 Development & Contribution Guidelines

Contributions to the Kukapay MCP Server are welcomed. To contribute:

1. Fork the Repository: Go to the repository and fork it for your own use.
2. Create an Issue: If you find a bug or have a feature request, raise an issue on GitHub.
3. Submit Pull Requests: Ensure your pull requests follow best practices and include clear documentation.

🌐 MCP Ecosystem & Resources

Explore more about Model Context Protocol and related projects within the MCP ecosystem:

• ModelContextProtocol.io
• Kukapay GitHub Repository

By leveraging the Kukapay MCP Server, developers can enhance their AI applications with real-time geolocation and time information, providing more contextual and personalized services to users.