Comprehensive flight planning, orbital mechanics, and spacecraft trajectory optimization platform with FastMCP integration and 30+ specialized aerospace tools.
Intelligent airport search, route planning, and aircraft performance modeling with real-time calculations.
Complete orbital mechanics suite with propagation, rendezvous planning, and trajectory optimization.
Advanced atmospheric modeling and aerodynamic analysis for comprehensive flight envelope studies.
3DOF trajectory simulation, sizing estimation, and thrust profile optimization for rocket systems.
Dual interface support with modern FastMCP framework and traditional REST API for maximum flexibility.
Specialized tools for propeller analysis, UAV optimization, and Monte Carlo uncertainty studies.
# Search for airports
# GET /airports/by_city?city=San Jose&country=US
curl "http://localhost:8080/airports/by_city?city=San Jose&country=US"
# Plan a flight
curl -X POST "http://localhost:8080/plan" \
-H "Content-Type: application/json" \
-d '{
"depart_city": "San Jose",
"arrive_city": "Tokyo",
"ac_type": "A320",
"cruise_alt_ft": 35000
}'
// Add to Claude Desktop configuration
{
"mcpServers": {
"aerospace-mcp": {
"command": "uv",
"args": ["run", "aerospace-mcp"],
"cwd": "/path/to/aerospace-mcp"
}
}
}
import requests
# Initialize client
base_url = "http://localhost:8080"
# Search airports
response = requests.get(
f"{base_url}/airports/by_city",
params={"city": "San Jose", "country": "US"}
)
airports = response.json()
# Plan flight
flight_data = {
"depart_city": "San Jose",
"arrive_city": "Tokyo",
"ac_type": "A320"
}
response = requests.post(f"{base_url}/plan", json=flight_data)
flight_plan = response.json()
Fastest Python package manager with excellent dependency resolution.
# Install UV
curl -LsSf https://astral.sh/uv/install.sh | sh
# Clone and setup
git clone https://github.com/cheesejaguar/aerospace-mcp.git
cd aerospace-mcp
uv venv && source .venv/bin/activate
uv sync
# Run HTTP server
uvicorn main:app --reload --host 0.0.0.0 --port 8080
Containerized deployment for consistent environments.
# Clone and build
git clone https://github.com/cheesejaguar/aerospace-mcp.git
cd aerospace-mcp
# Build and run
docker build -t aerospace-mcp .
docker run -p 8080:8080 aerospace-mcp
# Test the API
curl "http://localhost:8080/health"
Direct integration with Claude Desktop and other MCP clients.
# Run MCP server
uv run aerospace-mcp
# Or in TCP mode for debugging
uv run aerospace-mcp --tcp localhost:8000
# Test with MCP client
from mcp import Client
client = Client("stdio", "uv run aerospace-mcp")
THIS SOFTWARE IS FOR EDUCATIONAL, RESEARCH, AND DEVELOPMENT PURPOSES ONLY
• NOT FOR REAL NAVIGATION - Do not use for actual flight planning or navigation
• NOT CERTIFIED - This system is not certified by any aviation authority
• ESTIMATES ONLY - Performance calculations are theoretical estimates
• NO LIABILITY - Authors assume no responsibility for any consequences of use
For real flight planning, always use certified aviation software and consult official sources.