Aerospace MCP

Search for airports by IATA code or city name.

Args: query: IATA code (e.g., 'SJC') or city name (e.g., 'San Jose') country: Optional ISO country code to filter by (e.g., 'US', 'JP') query_type: Type of query - 'iata' for IATA codes, 'city' for city names, 'auto' to detect

Returns: Formatted string with airport information

Plan a flight route between two airports with performance estimates.

Args: departure: Dict with departure info (city, country, iata) arrival: Dict with arrival info (city, country, iata) aircraft: Optional aircraft config (ac_type, cruise_alt_ft, route_step_km) route_options: Optional route options

Returns: JSON string with flight plan details

Calculate great circle distance between two points.

Args: lat1: Latitude of first point in degrees lon1: Longitude of first point in degrees lat2: Latitude of second point in degrees lon2: Longitude of second point in degrees

Returns: JSON string with distance information

Get performance estimates for an aircraft type (requires OpenAP).

Args: aircraft_type: ICAO aircraft type code (e.g., 'A320', 'B737') distance_km: Flight distance in kilometers cruise_altitude_ft: Cruise altitude in feet

Returns: JSON string with performance estimates or error message

Get system status and capabilities.

Returns: JSON string with system status information

Get atmospheric properties (pressure, temperature, density) at specified altitudes using ISA model.

Args: altitudes_m: List of altitudes in meters model_type: Atmospheric model type ('ISA' for standard, 'enhanced' for extended)

Returns: Formatted string with atmospheric profile data

Calculate wind speeds at different altitudes using logarithmic or power law models.

Args: altitudes_m: List of altitudes in meters surface_wind_speed_ms: Wind speed at 10m reference height in m/s surface_wind_direction_deg: Wind direction at surface in degrees (0=North, 90=East) model_type: Wind model type ('logarithmic' or 'power_law') roughness_length_m: Surface roughness length in meters

Returns: Formatted string with wind profile data

Transform coordinates between reference frames (ECEF, ECI, ITRF, GCRS, GEODETIC).

Args: coordinates: Dict with coordinate data (format depends on frame) from_frame: Source reference frame to_frame: Target reference frame epoch_utc: Optional epoch for time-dependent transformations (ISO format)

Returns: JSON string with transformed coordinates

Convert geodetic coordinates (lat/lon/alt) to Earth-centered Earth-fixed (ECEF) coordinates.

Args: latitude_deg: Latitude in degrees (-90 to 90) longitude_deg: Longitude in degrees (-180 to 180) altitude_m: Altitude above WGS84 ellipsoid in meters

Returns: JSON string with ECEF coordinates

Convert ECEF coordinates to geodetic (lat/lon/alt) coordinates.

Args: x_m: X coordinate in meters y_m: Y coordinate in meters z_m: Z coordinate in meters

Returns: JSON string with geodetic coordinates

Analyze wing aerodynamics using Vortex Lattice Method or simplified lifting line theory.

Args: wing_config: Wing configuration (span_m, chord_m, sweep_deg, etc.) flight_conditions: Flight conditions (airspeed_ms, altitude_m, alpha_deg) analysis_options: Optional analysis settings

Returns: Formatted string with aerodynamic analysis results

Generate airfoil polar data (CL, CD, CM vs alpha) using database or advanced methods.

Args: airfoil_name: Airfoil name (e.g., 'NACA2412', 'NACA0012') reynolds_number: Reynolds number mach_number: Mach number alpha_range_deg: Optional angle of attack range, defaults to [-10, 20] deg

Returns: Formatted string with airfoil polar data

Calculate basic longitudinal stability derivatives for a wing.

Args: wing_config: Wing configuration parameters flight_conditions: Flight conditions

Returns: JSON string with stability derivatives

Get available airfoil database with aerodynamic coefficients.

Returns: JSON string with airfoil database

Analyze propeller performance using Blade Element Momentum Theory.

Args: propeller_geometry: Propeller geometry (diameter_m, pitch_m, num_blades, etc.) operating_conditions: Operating conditions (rpm_list, velocity_ms, altitude_m) analysis_options: Optional analysis settings

Returns: Formatted string with propeller performance analysis

Estimate UAV flight time and energy consumption for mission planning.

Args: uav_config: UAV configuration parameters battery_config: Battery configuration parameters mission_profile: Optional mission profile parameters

Returns: Formatted string with energy analysis results

Get available propeller database with geometric and performance data.

Returns: JSON string with propeller database

Calculate 3DOF rocket trajectory using numerical integration.

Args: rocket_geometry: Rocket geometry parameters launch_conditions: Launch conditions (launch_angle_deg, launch_site, etc.) simulation_options: Optional simulation settings

Returns: Formatted string with trajectory analysis results

Estimate rocket sizing requirements for target altitude and payload.

Args: target_altitude_m: Target altitude in meters payload_mass_kg: Payload mass in kg propellant_type: Propellant type ('solid' or 'liquid') design_margin: Design margin factor

Returns: JSON string with sizing estimates

Optimize rocket launch angle for maximum altitude or range.

Args: rocket_geometry: Rocket geometry parameters target_range_m: Optional target range in meters optimize_for: Optimization objective ('altitude' or 'range') angle_bounds_deg: Launch angle bounds in degrees

Returns: JSON string with optimization results

Convert orbital elements to state vector in J2000 frame.

Args: orbital_elements: Dict with orbital elements (semi_major_axis_m, eccentricity, etc.)

Returns: JSON string with state vector components

Convert state vector to classical orbital elements.

Args: state_vector: Dict with position_m and velocity_ms arrays

Returns: JSON string with orbital elements

Propagate orbit with J2 perturbations using numerical integration.

Args: initial_state: Initial orbital state (elements or state vector) propagation_time_s: Propagation time in seconds time_step_s: Integration time step in seconds

Returns: JSON string with propagated state

Calculate ground track from orbital state vectors.

Args: orbital_state: Orbital state (elements or state vector) duration_s: Duration for ground track calculation in seconds time_step_s: Time step for ground track points in seconds

Returns: JSON string with ground track coordinates

Calculate Hohmann transfer orbit parameters between two circular orbits.

Args: r1_m: Initial orbit radius in meters r2_m: Final orbit radius in meters

Returns: JSON string with transfer orbit parameters

Plan orbital rendezvous maneuvers between two spacecraft.

Args: chaser_elements: Chaser spacecraft orbital elements target_elements: Target spacecraft orbital elements rendezvous_options: Optional rendezvous planning parameters

Returns: JSON string with rendezvous plan

Optimize rocket thrust profile for better performance using trajectory optimization.

Args: rocket_geometry: Rocket geometry parameters burn_time_s: Burn time in seconds total_impulse_target: Target total impulse in N⋅s n_segments: Number of thrust segments objective: Optimization objective

Returns: JSON string with optimized thrust profile

Perform sensitivity analysis on rocket trajectory parameters.

Args: rocket_geometry: Baseline rocket geometry parameter_variations: Parameters to vary and their ranges analysis_options: Optional analysis settings

Returns: JSON string with sensitivity analysis results

Optimize spacecraft trajectory using genetic algorithm.

Args: optimization_problem: Problem definition (objective, constraints, variables) ga_parameters: Optional GA parameters (population_size, generations, etc.)

Returns: JSON string with optimization results

Optimize spacecraft trajectory using particle swarm optimization.

Args: optimization_problem: Problem definition (objective, constraints, variables) pso_parameters: Optional PSO parameters (n_particles, iterations, etc.)

Returns: JSON string with optimization results

Generate porkchop plot for interplanetary transfer opportunities.

Args: departure_body: Departure celestial body name arrival_body: Arrival celestial body name departure_date_range: Range of departure dates (ISO format) arrival_date_range: Range of arrival dates (ISO format) analysis_options: Optional analysis settings

Returns: JSON string with porkchop plot data

Perform Monte Carlo uncertainty analysis on spacecraft trajectory.

Args: nominal_trajectory: Nominal trajectory parameters uncertainty_parameters: Parameters with uncertainty distributions n_samples: Number of Monte Carlo samples analysis_options: Optional analysis settings

Returns: JSON string with uncertainty analysis results

Help format data in the correct format for a specific aerospace-mcp tool.

Uses GPT-5-Medium to analyze the user's requirements and raw data, then provides the correctly formatted parameters for the specified tool.

Args: tool_name: Name of the aerospace-mcp tool to format data for user_requirements: Description of what the user wants to accomplish raw_data: Any raw data that needs to be formatted (optional)

Returns: Formatted JSON string with the correct parameters for the tool

Help select the most appropriate aerospace-mcp tool for a given task.

Uses GPT-5-Medium to analyze the user's task and recommend the best tool(s) along with guidance on how to use them.

Args: user_task: Description of what the user wants to accomplish user_context: Additional context about the user's situation (optional)

Returns: Recommendation with tool name(s) and usage guidance