Simple Weather MCP Server Example from Quickstart

Overview: What is Simple Weather MCP Server?

The Simple Weather MCP Server is an example Node.js implementation of the Model Context Protocol (MCP) designed to provide weather data for various locations in the United States. This server serves as a foundational resource, enabling AI applications such as Claude Desktop and other MCP clients to access real-time weather updates through standard protocols. By adhering to MCP standards, this server ensures seamless integration with a wide range of AI tools, enhancing their functionality and utility.

🔧 Core Features & MCP Capabilities

The Simple Weather MCP Server supports two primary functionalities: obtaining weather alerts for US states and retrieving weather forecasts based on geographic coordinates (latitude and longitude). These capabilities are crucial for various applications that require current or predictive weather data. The server is structured to align with the MCP framework, ensuring compatibility and ease of use with a variety of MCP clients.

Weather Data Fetching

• Get-Alerts: Retrieves real-time weather alerts for specified US states using standardized input parameters.

  • Input: state (string): A two-letter US state code (e.g., CA, NY).

• Get-Forecast: Provides future weather conditions for a given location based on specific geographic coordinates.

  • Inputs:
    • latitude (number): The latitude of the location.
    • longitude (number): The longitude of the location.

⚙️ MCP Architecture & Protocol Implementation

The architecture of the Simple Weather MCP Server is designed to efficiently handle requests from MCP clients while adhering closely to MCP protocol standards. It leverages advanced Node.js capabilities, including npm packages for ease of integration and management.

Key Components

• Node.js Framework: Utilizes modern Node.js practices for backend development.
• npm Package: Uses the @h1deya/mcp-server-weather package for a streamlined installation process via npx.
• API Endpoints: Implemented according to MCP protocol specifications, ensuring compatibility and uniformity.

🚀 Getting Started with Installation

To start using the Simple Weather MCP Server, follow these steps:

Prerequisites

• Node.js: Ensure you have Node.js installed on your machine. You can download it from Nodejs.org.

Installation

1. Open a terminal or command prompt.

2. Clone this repository or navigate to the directory where you want to install the server.

3. Run the following command:

   npx @h1deya/mcp-server-weather
   

💡 Key Use Cases in AI Workflows

The Simple Weather MCP Server is particularly useful for applications and workflows that require real-time weather information, such as smart city projects, environmental monitoring systems, travel planning services, and climate research tools.

Use Case 1: Smart City Platform

In a smart city platform, the weather data can be integrated into traffic management systems to predict and mitigate potential hazards. For instance, if severe weather conditions are predicted (based on alerts), traffic signals might automatically adjust to reduce congestion.

Use Case 2: Travel Planning Tools

For travel planning tools like virtual assistants or apps, knowing future weather conditions is crucial for offering personalized suggestions. If the forecast predicts rain in a particular destination, travel recommendations could be adjusted to suggest indoor activities such as museums or galleries instead of outdoor ones.

🔌 Integration with MCP Clients

The Simple Weather MCP Server can be integrated seamlessly with multiple MCP clients due to its strict adherence to protocol standards. Below is an example configuration snippet to set up the server within Claude Desktop for MacOS and Windows users:

Installation Configuration Example

{
  "mcpServers": {
    "weather": {
      "command": "npx",
      "args": ["-y", "@h1deya/mcp-server-weather"],
      "env": {
        "API_KEY": "your-api-key"
      }
    }
  }
}

MCP Client Compatibility Matrix

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

📊 Performance & Compatibility Matrix

The performance of the Simple Weather MCP Server is designed to accommodate a wide range of usage scenarios:

• Latency: Sub-second response times for location-based queries ensure real-time data availability.
• Scalability: The server is optimized for efficient handling of multiple concurrent requests, making it suitable for both personal and large-scale applications.

🛠️ Advanced Configuration & Security

To configure the Simple Weather MCP Server more effectively or securely:

Environment Variables

Set environment variables such as API keys to ensure secure operation. For example:

API_KEY=YOUR_API_KEY_HERE_ENV_var

Security Best Practices

• Secure API Keys: Never expose your API keys publicly.
• Rate Limiting: Implement rate limits to prevent abuse and ensure fair usage.

❓ Frequently Asked Questions (FAQ)

1. Q: How do I secure my Simple Weather MCP Server?

   • A: Secure your server by setting up environment variables for sensitive information such as API keys, enabling rate limiting, and using HTTPS to encrypt data in transit.

2. Q: Can the server provide historical weather data?

   • A: Currently, this server focuses on real-time and forecasted data. For historical data retrieval, consider integrating with other sources or building an additional service.

3. Q: Is there a way to customize the weather alerts for specific events?

   • A: The get-alerts function can be customized by modifying the underlying logic or integrating custom alert conditions based on user-defined parameters.

4. Q: How does this server handle edge cases like handling non-numeric latitude and longitude inputs?

   • A: The server includes validation to ensure that only valid geographic coordinates are processed, preventing errors and improving overall robustness.

5. Q: Can I extend the functionality of this server in the future?

   • A: Absolutely! You can extend or adapt the server by adding more features such as weather history tracking, climate change pattern analysis, or even integrating additional data sources like satellite imagery.

👨‍💻 Development & Contribution Guidelines

Contributions to this project are encouraged and can significantly improve its functionality. Follow these steps to get started:

1. Fork the Repository: Head over to GitHub and fork the repository.
2. Clone the Project: Clone your forked repository to your local machine.
3. Create a New Feature Branch: Name it appropriately (e.g., add-new-feature).
4. Make Your Changes: Edit code, update documentation, or make necessary improvements.
5. Commit and Push: Commit changes and push them back up to your fork.
6. Submit a Pull Request: Create a pull request explaining the changes you've made.

🌐 MCP Ecosystem & Resources

The Simple Weather MCP Server is part of an expanding ecosystem aimed at standardizing access methods for data providers, developers, and AI application users. Explore more resources related to MCP by visiting:

• MCP Quickstart Guide
• Model Context Protocol Documentation
• GitHub Repository for further examples and discussions.

---

MCP Protocol Flow Diagram

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

MCP Client Compatibility Matrix

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

By following these guidelines and integrating the Simple Weather MCP Server, developers can enhance their AI applications with rich weather data integrations, improving user experience and functionality.