UBOS Asset Marketplace: Satellite Tracking MCP Server - Your Gateway to Real-Time Space Data

In the ever-evolving landscape of AI-driven applications, the need for reliable and accessible real-time data is paramount. UBOS is at the forefront of this revolution, offering a comprehensive AI Agent Development Platform that empowers businesses to orchestrate AI Agents, seamlessly connect them with enterprise data, and construct bespoke AI Agents utilizing Large Language Models (LLMs) and Multi-Agent Systems.

Within the UBOS ecosystem, the Satellite Tracking MCP Server emerges as a critical asset, enabling AI models to tap into the dynamic world of satellite data. This Model Context Protocol (MCP) server acts as a bridge, providing AI models with access to invaluable satellite tracking information through the N2YO API. Whether you’re involved in logistics, weather forecasting, scientific research, or simply fascinated by the cosmos, this server unlocks a universe of possibilities.

What is an MCP Server and Why Does It Matter?

Before we delve into the specifics of the Satellite Tracking MCP Server, let’s first understand the underlying concept of an MCP Server. MCP stands for Model Context Protocol. It’s an open protocol designed to standardize how applications provide context to LLMs.

Think of an MCP server as a translator or intermediary. It takes requests from an AI model, translates them into a language that an external data source (like the N2YO API) can understand, retrieves the requested information, and then translates that information back into a format that the AI model can readily use.

This standardization is crucial for several reasons:

• Simplifies Integration: It eliminates the need for AI developers to write custom code for each individual data source they want to connect to. The MCP server provides a consistent interface.
• Enhances Flexibility: It allows AI models to access a wider range of data sources and tools, broadening their capabilities and improving their accuracy.
• Promotes Reusability: Once an MCP server is built for a specific data source, it can be used by multiple AI models and applications.

Use Cases: Where Can Satellite Tracking MCP Server Make a Difference?

The Satellite Tracking MCP Server opens doors to a diverse range of applications across various industries. Here are just a few examples:

• Logistics and Transportation: Track the real-time location of cargo ships, airplanes, and other vehicles that rely on satellite-based navigation systems. Optimize routes, predict arrival times, and improve overall efficiency.
• Weather Forecasting: Access satellite imagery and data to enhance weather models and improve the accuracy of weather forecasts. Monitor storm patterns, track cloud formations, and predict precipitation.
• Agriculture: Utilize satellite data to monitor crop health, assess irrigation needs, and optimize fertilizer application. Improve crop yields and reduce resource waste.
• Disaster Response: Track the movement of emergency vehicles and personnel during natural disasters. Assess damage, identify affected areas, and coordinate relief efforts.
• Scientific Research: Access satellite data for a wide range of scientific research projects, including climate change studies, environmental monitoring, and space exploration.
• Education: Integrate satellite data into educational programs to teach students about space, science, and technology. Inspire the next generation of scientists and engineers.
• Amateur Radio: Predict satellite passes for amateur radio communications.
• Aerospace: Monitor the position and status of satellites, which is helpful for space situational awareness.

Key Features: What Does the Satellite Tracking MCP Server Offer?

The Satellite Tracking MCP Server is packed with features designed to provide comprehensive access to satellite tracking data. Here’s a closer look at what it offers:

• Real-Time Satellite Position: Obtain the precise, up-to-the-minute location of any satellite by its NORAD ID. This feature is essential for applications that require real-time tracking, such as logistics and disaster response.
• TLE (Two-Line Element) Data: Access the TLE data for a satellite, which contains the orbital parameters needed to calculate its position at any given time. This data is crucial for predicting future satellite movements.
• Predict Visual Passes: Determine when a satellite will be visible from a specific location on Earth. This feature is useful for amateur astronomers, satellite enthusiasts, and anyone who wants to witness the beauty of a satellite passing overhead.
• Predict Radio Passes: Identify the times when a satellite will be within radio communication range of a specific location. This feature is essential for amateur radio operators and anyone who needs to communicate with satellites.
• Satellites Above Location: Discover which satellites are currently above a specified location. This feature is useful for identifying potential communication partners or for monitoring satellite activity in a particular region.
• Search Satellites: Quickly and easily search for satellites by name or category. This feature makes it easy to find the satellites you’re interested in, even if you don’t know their NORAD IDs.
• Resource Access: Access detailed information about a satellite through a dedicated resource URI.
• Satellite Categories: Filter satellite data by category, such as amateur, CubeSat, education, and more.

Installation and Configuration: Getting Started with the Satellite Tracking MCP Server

Setting up the Satellite Tracking MCP Server is a straightforward process. Here’s a step-by-step guide:

1. Prerequisites: Ensure you have Node.js 18 or higher installed on your system. You’ll also need an N2YO API key, which you can obtain from N2YO API Services.

2. Clone the Repository: Clone the repository from its source (likely a Git repository) or download the source code as a ZIP file.

3. Install Dependencies: Navigate to the project directory in your terminal and run npm install to install all the necessary dependencies.

4. Build the Server: Run npm run build to build the server. This will compile the code and prepare it for execution.

5. Configure the API Key: Set the N2YO_API_KEY environment variable to your N2YO API key. This is essential for the server to access the N2YO API.

6. MCP Settings Configuration: Integrate the server into your Claude MCP settings configuration file. This involves specifying the command to run the server, the arguments to pass to the command, and the environment variables to set.

   • For Claude Desktop App (macOS): Edit ~/Library/Application Support/Claude/claude_desktop_config.json.
   • For Claude VSCode Extension: Edit ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json.

   The configuration should look something like this:

   { “mcpServers”: { “satellite-tracking”: { “command”: “node”, “args”: [“/path/to/satellite-tracking-server/build/index.js”], “env”: { “N2YO_API_KEY”: “your-api-key-here” }, “disabled”: false, “autoApprove”: [] } } }

   Important: Replace /path/to/satellite-tracking-server/build/index.js with the actual path to the server’s entry point and your-api-key-here with your actual N2YO API key.

Usage Examples: Putting the Satellite Tracking MCP Server to Work

Once the server is configured and running, you can start using it to access satellite tracking data. Here are some examples of how to interact with the server:

• Get Satellite Position:

  <use_mcp_tool> <server_name>satellite-tracking</server_name> <tool_name>get_satellite_position</tool_name>{ “norad_id”: 25544, “observer_lat”: 40.7128, “observer_lng”: -74.0060 }</use_mcp_tool>

• Get Satellite TLE Data:

  <use_mcp_tool> <server_name>satellite-tracking</server_name> <tool_name>get_satellite_tle</tool_name>{ “norad_id”: 25544 }</use_mcp_tool>

• Predict Visual Passes:

  <use_mcp_tool> <server_name>satellite-tracking</server_name> <tool_name>predict_visual_passes</tool_name>{ “norad_id”: 25544, “observer_lat”: 40.7128, “observer_lng”: -74.0060, “days”: 7 }</use_mcp_tool>

• Search for Satellites:

  <use_mcp_tool> <server_name>satellite-tracking</server_name> <tool_name>search_satellites</tool_name>{ “query”: “ISS” }</use_mcp_tool>

• Get Satellites Above Location:

  <use_mcp_tool> <server_name>satellite-tracking</server_name> <tool_name>get_satellites_above</tool_name>{ “observer_lat”: 40.7128, “observer_lng”: -74.0060, “search_radius”: 45 }</use_mcp_tool>

• Access Satellite Resource:

  <access_mcp_resource> <server_name>satellite-tracking</server_name> satellite://25544 </access_mcp_resource>

API Key Limitations: Understanding the N2YO API Usage Limits

It’s important to be aware of the limitations imposed by the N2YO API, particularly the usage limits based on your subscription plan. The free tier, for example, typically allows:

• 1,000 requests per hour
• Basic functionality across all endpoints

Exceeding these limits may result in errors or service disruptions. Keep track of your API usage to avoid any issues.

Troubleshooting: Addressing Common Issues

Here are some common issues you might encounter and how to resolve them:

• API Key Errors: Double-check that your N2YO API key is valid and correctly set in the environment variables.
• Rate Limiting: If you encounter rate limiting errors, the server will automatically retry with exponential backoff. However, you may need to wait before making additional requests.
• No Data Found: Some satellites, especially older or inactive ones, may not have real-time tracking data available.

UBOS: Your Partner in AI Agent Development

The Satellite Tracking MCP Server is just one example of the many valuable assets available on the UBOS platform. We are committed to providing developers with the tools and resources they need to build powerful and innovative AI-driven applications. From data connectors to pre-built agents to a comprehensive development environment, UBOS has everything you need to bring your AI vision to life.

Join the UBOS community today and unlock the full potential of AI!