"Reading Local Project Files to Assist Development" matching MCP servers:

Connects AI agents to MAVLink drones (PX4, ArduPilot) via a capability layer with safety guardrails, enabling telemetry, flight control, and mission management through natural language.

Maintained fork of Three-Little-Birds/openvsp-mcp, adding OpenVSP geometry inspection, typed parameter editing, SVG/STL previews, validated VSPAERO analysis, and durable parallel batches with progress, cancellation, resume, and CSV/JSON export. Independently maintained by rhyne1012; not an official OpenVSP or NASA project.

Provides deterministic computation of magnetic declination and sky positions (sun, moon, planets) for any location and time, enabling agents to get accurate ephemeris and geomagnetic data without hallucination.

Enables AI agents to run Link Budget, Radar Range, and EO/IR calculations and to read the user's saved projects by exchanging request and result files through a local folder that the macOS/iPadOS engineering calculator app watches. All computation happens in the app, and results are returned verbatim, including undetermined outcomes that report missing inputs.

A local, open-source MCP server that wraps astronomy data services (SIMBAD, JPL Horizons, VizieR, etc.) behind a conversational interface, enabling AI assistants to answer astronomy questions with real, typed, and provenance-tracked data.

Enables MCP clients to search, read, and cite the EASA Easy Access Rules with exact rule references, metadata, and linked AMC/GM. It covers aircrew, air operations, SERA, sailplanes, balloons, continuing airworthiness, basic regulation, drones, and aerodromes, returning ranked results and full rule text.

US drone airspace intelligence and mission planning. 24 MCP tools: check airspace restrictions across 11 FAA data layers, plan grid/orbit/corridor surveys, validate Part 107 compliance, generate pre-flight briefings, and export to KML/GPX/QGC/Litchi/WPML.

Enables AI agents to autonomously write, run, and debug NASA GMAT mission scripts, with tools for script execution, curated knowledge of common pitfalls, and semantic documentation search.

Connects AI coding agents to Microsoft Flight Simulator via SimConnect, enabling full read/write access to SimVars, L-vars, events, calculator code execution, and embedded documentation for add-on development.

Provides smart URL navigation to ANSYS Fluent documentation, enabling AI assistants to quickly find relevant help pages and manual sections.

Enables running reproducible AVL 3.52 aerodynamic analyses through MCP, with input validation, isolated execution, sweeps, background jobs, and structured results including solver files.

Provides LLM access to the Event Monitoring System (EMS) API for comprehensive flight data analytics and monitoring. It enables users to query flight records, retrieve time-series analytics, and explore aircraft assets or database hierarchies.

Enables LLMs and AI agents to interact with AFSIM through standardized MCP tools for scenario management, entity/component control, simulation execution, and results analysis.

Official bounded, read-only access to live community-powered aircraft positions and aggregate ADSBiq network statistics.

Enables authenticated access to a pilot's flight-planning account, letting an assistant search installed airfield charts offline, pull full airfield records with pilot notes and live feedback, and list, read, or download flightplans from local disk or cloud storage.

Exposes the astrodynamics capabilities of the Brahe library enabling language models to perform space situational awareness and astrodynamics calculations.

Enables automated geometry editing and aerodynamic analysis using OpenVSP and VSPAero through natural language. Provides tools to modify aircraft geometry parameters and run computational fluid dynamics simulations programmatically.

Provides seamless integration with NASA's public APIs, enabling AI assistants to access space and astronomy data including APOD, Mars rover photos, Near-Earth Objects, space weather events, and Earth imagery.

Enables external agents to define and execute read-only derived properties over an ontology by analyzing field requests, validating link cardinality, and generating Semantic Join SQL within a three-hop neighborhood.

Enables AI assistants to interact with Yamcs mission control systems through natural language, providing tools and resources for telemetry, commands, links, storage, instances, and alarms.