"Creating an application" matching MCP servers:

An MCP-powered AI platform for satellite mission control, enabling space weather analysis, orbital collision detection, satellite health monitoring, and secure command validation through natural language.

Provides AI assistants with live information about who is currently in space and the location of the ISS, using the free Open Notify API.

An MCP server that lets AI agents search, save, preview, download, and cart satellite scenes from ISRO's Bhoonidhi portal in natural language, with search and saved queries requiring no login and downloads/cart operations using an out-of-band session.

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.

Enables requirement-level question answering over your own ECSS and NASA space standards documents, returning exact citations to the document, issue and requirement ID or an explicit "not covered". It offers tools for listing loaded documents, fetching requirements by ID, keyword-searching requirements and table rows, reading tables, tracing references, comparing a topic across standards, and retrieving section outlines.

Enables managing services on OpenWrt, ImmortalWrt, and systemd-based routers via SSH, with read-only service listing, status, and log queries, plus write operations (start/stop/restart) requiring confirmationional confirmation and an optional shell execution capability.

Turns any MCP client into an OpenFOAM setup and debugging co-pilot, enabling case scaffolding, dictionary edits, mesh sizing, inlet turbulence calculations, and solver-log convergence checks through natural language.

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.

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 any MCP client to plan and run verifiable analysis of engine hot-fire and bench test data through tools that open runs, segment phases, check sensor health, redlines, valve response and oscillations, compare simulations, verify every reported number against an evidence ledger, and write HTML reports. All findings stay traceable and reproducible from deterministic tool calls rather than raw samples.

Provides standardized access to 20+ NASA data sources including astronomy pictures, Mars rover photos, near-Earth objects, satellite imagery, space weather, and planetary data through a unified interface optimized for AI consumption.

Enables an MCP client to drive CST Studio Suite 2026 through its official Python automation API, covering 3D modelling, materials, ports, boundaries, mesh and solver configuration, solver runs, and result reading. Also provides verification and export tools — S11, reference impedance, port diagnostics, energy budget and model audit — plus Touchstone/ASCII/JSON evidence output and parameter sweeps, all locally over stdio.

MCP server for inspecting PX4 ULog flight logs, enabling AI assistants to understand, debug, and reason about drone systems.

Enables AI agents to interact with an ArduPilot vehicle in real-time via MAVLink, including reading state, inspecting and changing parameters, switching flight modes, diagnosing arming failures, and gated arming/disarming.

An MCP server that equips LLM clients with authoritative astrodynamics tools including TLE/SGP4 propagation, Lambert solving, ground-station access, time-scale and coordinate-frame conversions, and more.

An MCP server that lets an LLM operate an amateur radio shack: query live APRS traffic, predict satellite passes, schedule SDR captures, and monitor FT8/WSPR band activity.

Enables an AI assistant to poll a queue of alerts about watched spacecraft contacting Earth via NASA's Deep Space Network and acknowledge them once reported. It also lets users manage a watchlist, mute craft, and inspect feed freshness, all through pull-based MCP tools.

Turns an AI assistant into an OpenFOAM setup and debugging co-pilot, enabling case scaffolding, dictionary edits, mesh sizing, turbulence calculations, and solver log analysis through natural language.

Provides the JSBSim flight-dynamics engine as an MCP service, enabling AI agents to control and simulate aircraft in real-time through natural language.

Enables ArduPilot drone control through MAVSDK plugins, supporting mission upload, telemetry, and flight commands via MCP tools.