"An overview of knowledge graphs" 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.

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.

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 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.

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.

Enables configuration, diagnostics, and troubleshooting of iNAV fixed-wing flight controllers over USB via Claude.

Enables an LLM to build S1000D data modules and publication modules from structured drafts and numbering rules instead of writing XML, verifying results against XSD, BREX and references and applying only unambiguous fixes. It also supports converting experiential manuals, extracting and restoring translatable segments, creating comment modules, and writing nothing by default.

Enables read-only querying of orbital launch and space-sector data plus testnet event-market listings, order books, midpoint prices, and cancel-safety checks on Base Sepolia. It does not place, cancel, or claim orders, and it never resolves markets.

Enables AI clients to search a bilingual glossary of Earth-Moon space terms by keyword and retrieve individual entries with full definitions, references, and page links through two read-only MCP tools. It covers 720 terms across 8 categories.

MCP server for space weather and HF propagation conditions — live solar flux, Kp index, DSCOVR solar wind, X-ray flux, alerts, 27-day forecast, and band-by-band outlook through any MCP-compatible AI assistant.

Enables an LLM to read S1000D BREX data modules and check data modules against them, reporting allowed elements, values, SNS code meanings, and permitted illustration formats. Also returns each rule violation with its XPath location, actual value, rule ID, and severity, following the BREX reference chain layer by layer.

Enables an LLM to check S1000D data modules through XML schema validation, BREX rule checks, and reference resolution, returning an evidence-backed combined verification status per data module or across a whole CSDB folder.

This server allows Large Language Models to consume S1000D data and publication modules as structured information instead of raw XML. It enables reading the content's hierarchy, applicability to specific products, and document verification status.

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 natural language analysis of ArduPilot flight logs (.bin files) via AI chat apps like Claude Desktop, Cursor, and VS Code, providing explanations and answering questions about flight issues.

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.

Lets an MCP client read PX4 SITL .ulg logs and answer why a flight failed or underperformed — failsafes, arming reasons, estimator validity versus simulator ground truth, and how late PX4 followed offboard velocity setpoints. It also lists, searches, scans and plots topics, messages and parameters across logs, replacing hand-written pyulog scripts.

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 retrieval of CelesTrak satellite pass predictions, NOAA space weather Kp observations and alerts, and conversion of ICAO NOTAM Q-line notices into GeoJSON bounding envelopes through MCP tools.

Provides MCP tools for CPACS-oriented TiGL workflows, enabling lifecycle management, inspection, export, and parameter manipulation of aircraft geometry models without native geometry runtimes.

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.

Windsock aircraft intelligence for AI agents: stdio bridge (npm windsock-mcp / PyPI windsock-mcp) to the hosted Windsock MCP server with 38 tools for aircraft valuations, FAA registry lookup, cost of ownership, comparable aircraft, ADs/STCs, market metrics, reports and logbooks.

Enables querying the NASA MAST archive of space telescopes for astronomical data, including cone searches, mission-specific queries, and target name resolution.

Enables retrieval of satellite vegetation statistics (NDVI) and searches of Sentinel-2 scene catalogs, returning results as JSON.