Weather & DigitalOcean MCP Servers: Enhancing Data Integration and Deployment Capabilities

Overview: What are Weather & DigitalOcean MCP Servers?

Weather & DigitalOcean Model Context Protocol (MCP) servers form a vital component in the broader ecosystem of AI applications, leveraging standardized protocols to ensure interoperability. These servers provide essential capabilities for retrieving real-time weather information and managing static websites on digital platforms, respectively.

🔧 Core Features & MCP Capabilities

Weather MCP Server

The Weather MCP server integrates with the National Weather Service API to fetch and deliver weather data. It supports two key functionalities:

• Get Alerts: Retrieves weather alerts for a specified US state.
• Get Forecast: Provides a comprehensive weather forecast based on geographical coordinates.

Both operations require minimal input, ensuring easy and efficient utilization by AI applications such as Claude Desktop, Continue, and Cursor.

DigitalOcean MCP Server

The DigitalOcean MCP server offers advanced tools to deploy and manage static websites on the DigitalOcean App Platform. Key features include:

• Deploy Static Site: Simplifies the process of pushing a website from GitHub repositories.
• Get App Info: Retrieves detailed information about an existing app.
• List Deployments & Get Deployment Status: Monitors and manages ongoing deployment processes.

⚙️ MCP Architecture & Protocol Implementation

Both Weather and DigitalOcean servers align with Model Context Protocol (MCP) standards, ensuring seamless integration across different AI applications. The core architecture involves:

1. API Utilization: Shared API functions manage communication between clients and server layers.
2. Server Configuration: Detailed configurations ensure secure and functional operations.

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

🚀 Getting Started with Installation

Project Setup

1. Clone the repository:

   git clone https://github.com/yourusername/weather-and-digitalocean-mcp-servers.git
   

2. Install dependencies:

   npm install
   

Building and Running Servers

• To run the Weather MCP server:

  node build/index.js weather
  

• To run the DigitalOcean MCP server:

  node build/index.js digitalocean
  

💡 Key Use Cases in AI Workflows

Real-World Case Study: Weather Integration with AI Applications

Assume an AI chatbot integrated into Cursor, leveraging the Weather MCP server to provide timely weather updates and alerts. This feature not only enhances user experience but also ensures accuracy through direct API data feeds.

Real-World Case Study: Deployment Automation with DigitalOcean

A content management system (CMS) built for a small business automates static website deployment via the DigitalOcean MCP server. By integrating this server, the enterprise can streamline development cycles and reduce manual labor significantly.

🔌 Integration with MCP Clients

For developers looking to integrate these servers into their applications:

{
  "mcpServers": {
    "weather": {
      "command": "node",
      "args": [
        "/path/to/your/project/build/index.js"
      ]
    },
    "digitalocean": {
      "command": "node",
      "args": [
        "/path/to/your/project/build/index.js",
        "digitalocean"
      ]
    }
  }
}

📊 Performance & Compatibility Matrix

While these servers are designed for compatibility:

• Claude Desktop: Full support.
• Continue: Fully supported.
• Cursor: Supports core data functionalities, albeit with limited prompt capabilities due to internal implementation constraints.

🛠️ Advanced Configuration & Security

Environment Variables

DO_API_TOKEN=your_digitalocean_api_token
API_KEY=your_weather_service_key

Configuring MCP Clients

Ensure your .cursor/mcp.json file reflects the correct configurations:

{
  "mcpServers": {
    "weather": {
      "command": "node",
      "args": [
        "/path/to/your/project/build/index.js"
      ],
      "env": {
        "API_KEY": "your_weather_service_key"
      }
    },
    "digitalocean": {
      "command": "node",
      "args": [
        "/path/to/your/project/build/index.js",
        "digitalocean"
      ],
      "env": {
        "DO_API_TOKEN": "your_digitalocean_api_token"
      }
    }
  }
}

❓ Frequently Asked Questions (FAQ)

1. How do I configure the API tokens?
   • Tokens can be set as environment variables, passed via command-line arguments, or stored in specific config files.
2. Can I use these servers with Cursor?
   • Yes, but full support for prompts and resources might not be available due to internal limitations.
3. What's the default deployment region for DigitalOcean?
   • The default region is set to "nyc," which can be overwritten during deploy-static-site operations.
4. How do I deploy a website with custom domain?
   • Use the custom_domain parameter when deploying:

     node build/index.js digitalocean --app_name myapp --repo user/repo --custom_domain=mywebsite.com
     

5. Are these servers compatible with other MCP clients besides the ones mentioned?
   • Yes, but comprehensive testing across all clients is recommended to ensure full functionality.

👨‍💻 Development & Contribution Guidelines

Contributions are highly appreciated and can be made by following:

1. Forking the repository.
2. Creating a new branch for your feature or bug fix.
3. Committing changes with descriptive messages.
4. Pushing your local commits to GitHub.
5. Creating a pull request.

🌐 MCP Ecosystem & Resources

Additional resources and documentation can be found at:

• Model Context Project Documentation
• MCP Client Examples

By incorporating these servers into your AI application, you significantly enhance its capability to interact with diverse data sources and tools, thereby expanding the scope of intelligent and dynamic applications.