How do I use Satellite MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Satellite MCP Server when will the ISS be visible from Tokyo tomorrow?" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

Satellite MCP Server

A comprehensive Model Context Protocol (MCP) server for satellite orbital mechanics calculations with natural language processing capabilities.

✨ Key Features

🛰️ Satellite Access Window Calculations - Calculate when satellites are visible from ground locations
🌍 World Cities Database - Built-in database of 200+ cities worldwide for easy location lookup
🗣️ Natural Language Processing - Parse orbital parameters from text like "satellite at 700km in SSO over London"
📡 TLE Generation - Generate Two-Line Elements from orbital descriptions
🌅 Lighting Analysis - Ground and satellite lighting conditions (civil, nautical, astronomical twilight)
📊 Bulk Processing - Process multiple satellites and locations from CSV data
🚀 6 Orbit Types - Support for LEO, MEO, GEO, SSO, Molniya, and Polar orbits

🚀 Quick Start

Using Docker (Recommended)

# Clone the repository git clone <repository-url> cd mcp-orbit # Build the Docker image make docker-build # Run the MCP server make docker-run

Local Installation

# Install dependencies make install # Run the MCP server make run

🔌 Connecting to the MCP Server

The server communicates via JSON-RPC 2.0 over stdio. Here are the connection methods:

Claude Desktop Integration

Add to your Claude Desktop MCP configuration file:

macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%/Claude/claude_desktop_config.json

{ "mcpServers": { "satellite-mcp-server": { "command": "docker", "args": ["run", "--rm", "-i", "satellite-mcp-server:latest"] } } }

Direct Docker Connection

# Interactive mode docker run -it --rm satellite-mcp-server:latest # Pipe commands echo '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}' | \ docker run --rm -i satellite-mcp-server:latest

Local Python Connection

# If running locally without Docker python -m src.mcp_server

💬 Example Usage in LLMs

Example 1: Basic Satellite Pass Prediction

User Prompt:

"When will the ISS be visible from London tomorrow?"

MCP Tool Call:

{ "tool": "calculate_access_windows_by_city", "arguments": { "city_name": "London", "tle_line1": "1 25544U 98067A 24001.50000000 .00001234 00000-0 12345-4 0 9999", "tle_line2": "2 25544 51.6400 123.4567 0001234 12.3456 347.6543 15.49011999123456", "start_time": "2024-01-02T00:00:00Z", "end_time": "2024-01-03T00:00:00Z" } }

Response: The ISS will be visible from London 4 times tomorrow, with the best pass at 19:45 UTC reaching 78° elevation in the southwest sky during civil twilight.

Example 2: Natural Language Orbital Design

User Prompt:

"Create a sun-synchronous satellite at 700km altitude and show me when it passes over Tokyo."

MCP Tool Calls:

Parse orbital elements:

{ "tool": "parse_orbital_elements", "arguments": { "orbital_text": "sun-synchronous satellite at 700km altitude" } }

Calculate access windows:

{ "tool": "calculate_access_windows_from_orbital_elements_by_city", "arguments": { "orbital_text": "sun-synchronous satellite at 700km altitude", "city_name": "Tokyo", "start_time": "2024-01-01T00:00:00Z", "end_time": "2024-01-02T00:00:00Z" } }

Response: Generated SSO satellite (98.16° inclination, 98.6 min period) with 14 passes over Tokyo in 24 hours, including 6 daylight passes and 8 during various twilight conditions.

Example 3: Bulk Satellite Analysis

User Prompt:

"I have a CSV file with ground stations and want to analyze coverage for multiple satellites."

MCP Tool Call:

{ "tool": "calculate_bulk_access_windows", "arguments": { "locations_csv": "name,latitude,longitude,altitude\nMIT,42.3601,-71.0589,43\nCaltechm,34.1377,-118.1253,237", "satellites_csv": "name,tle_line1,tle_line2\nISS,1 25544U...,2 25544...\nHubble,1 20580U...,2 20580...", "start_time": "2024-01-01T00:00:00Z", "end_time": "2024-01-02T00:00:00Z" } }

🛠️ Available Tools

calculate_access_windows - Basic satellite visibility calculations
calculate_access_windows_by_city - City-based satellite passes
calculate_bulk_access_windows - Multi-satellite/location analysis
parse_orbital_elements - Natural language orbital parameter parsing
calculate_access_windows_from_orbital_elements - Access windows from orbital text
calculate_access_windows_from_orbital_elements_by_city - Combined orbital elements + city lookup
search_cities - Find cities in the world database
validate_tle - Validate Two-Line Element data
get_orbit_types - Available orbit type definitions

🗂️ Project Structure

/ ├── src/ │ ├── mcp_server.py # MCP server implementation │ ├── satellite_calc.py # Core orbital mechanics calculations │ └── world_cities.py # World cities database ├── docs/ # Documentation ├── Dockerfile # Container definition ├── docker-compose.yml # Multi-container setup └── Makefile # Build automation

📚 Dependencies

Skyfield - Satellite position calculations
NumPy - Numerical computations
MCP - Model Context Protocol implementation
Python 3.8+ - Runtime environment

🤝 Contributing

This is a specialized MCP server for satellite orbital mechanics. For issues or enhancements, please check the documentation in the docs/ directory.

📄 License

[Add your license information here]

Satellite MCP Server

Satellite MCP Server

✨ Key Features

🚀 Quick Start

Using Docker (Recommended)

Local Installation

🔌 Connecting to the MCP Server

Claude Desktop Integration

Direct Docker Connection

Local Python Connection

💬 Example Usage in LLMs

Example 1: Basic Satellite Pass Prediction

Example 2: Natural Language Orbital Design

Example 3: Bulk Satellite Analysis

🛠️ Available Tools

🗂️ Project Structure

📚 Dependencies

🤝 Contributing

📄 License

Resources

New MCP Servers

Latest Blog Posts

MCP directory API