Satellite MCP Server
About
Performs satellite orbital mechanics calculations using natural language, with a built-in world cities database for location lookup.
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- buildaspacepro
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Setup
Install Satellite MCP Server in your MCP client (Claude Desktop, Cursor, Windsurf, and others).
Repository: https://github.com/buildaspacepro/Orbit-MCP
Follow the installation instructions in the repository README, then restart your MCP client.
A comprehensive Model Context Protocol (MCP) server for satellite orbital mechanics calculations with natural language processing capabilities.
- π°οΈ Satellite Access Window Calculations- Calculate when satellites are visible from ground locations
- π World Cities Database- Built-in database of 200+ cities worldwide for easy location lookup
- π£οΈ Natural Language Processing- Parse orbital parameters from text like "satellite at 700km in SSO over London"
- π‘ TLE Generation- Generate Two-Line Elements from orbital descriptions
- π
Lighting Analysis- Ground and satellite lighting conditions (civil, nautical, astronomical twilight)
- π Bulk Processing- Process multiple satellites and locations from CSV data
- π 6 Orbit Types- Support for LEO, MEO, GEO, SSO, Molniya, and Polar orbits
# Clone the repository git clone <repository-url> cd mcp-orbit # Build the Docker image make docker-build # Run the MCP server make docker-run
# Install dependencies make install # Run the MCP server make run
The server communicates via JSON-RPC 2.0 over stdio. Here are the connection methods:
Add to your Claude Desktop MCP configuration file:
macOS:~/Library/Application Support/Claude/claude_desktop_config.jsonWindows:%APPDATA%/Claude/claude_desktop_config.json
{ "mcpServers": { "satellite-mcp-server": { "command": "docker", "args": ["run", "--rm", "-i", "satellite-mcp-server:latest"] } } }
# 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
# If running locally without Docker python -m src.mcp_server
Example 1: Basic Satellite Pass Prediction
"When will the ISS be visible from London tomorrow?"
{ "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 78Β° elevation in the southwest sky during civil twilight.
Example 2: Natural Language Orbital Design
"Create a sun-synchronous satellite at 700km altitude and show me when it passes over Tokyo."
{ "tool": "parse_orbital_elements", "arguments": { "orbital_text": "sun-synchronous satellite at 700km altitude" } }
{ "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 (98.16Β° inclination, 98.6 min period) with 14 passes over Tokyo in 24 hours, including 6 daylight passes and 8 during various twilight conditions.
"I have a CSV file with ground stations and want to analyze coverage for multiple satellites."
{ "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" } }
- 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
/ βββ src/ β βββ mcp_server.py # MCP server implementation β βββ satellite_calc.py # Core orbital mechanics calculations β βββ world_cities.py # World cities database βββ docs/ # Documentation βββ Dockerfile # Container definition βββ docker-compose.yml # Multi-container setup βββ Makefile # Build automation
- Skyfield- Satellite position calculations
- NumPy- Numerical computations
- MCP- Model Context Protocol implementation
- Python 3.8+- Runtime environment
This is a specialized MCP server for satellite orbital mechanics. For issues or enhancements, please check the documentation in thedocs/directory.
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