"Getting the Most Out of Jina Framework" matching MCP servers:

MCP server for controlling satellite ground station operations in the Trench simulation, including pass management, downlink control, and antenna pointing.

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.

A lightweight MCP server that provides analytics on SpaceX launches, including launch counts per year, success vs failure totals, and most-used launch site.

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

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.

Live space data for AI agents: upcoming rocket launches (SpaceX, NASA, Rocket Lab…), ISS pass predictions for any city or coordinates (live SGP4), and launch news in 7 languages. Read-only, no auth, no API key. Backed by gocosmik.com — the free real-time 3D satellite tracker.

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.

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.

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

Search 419,000+ LLM-extracted space regulatory filings from the FCC, ITU, UNOOSA, and FAA. Semantic search, entity dossiers, spectrum-band holdings, launch licenses, filing trends, and alerts.

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.

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

Enables wing simulation and aerodynamic analysis for pterosaur-inspired flight models. Provides lift, drag, and thrust calculations through the pterasim module with analytical fallbacks when the native module is unavailable.

Enables running avian flight dynamics simulations through the Flappy simulator. Provides typed configuration models and deterministic fallback calculations for bird flight analysis.

Provides access to live SpaceX data including latest launches, upcoming launches, and company information through the SpaceX API.

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.

MCP server for the INDIGO astronomy automation protocol, enabling AI agents to control telescopes, cameras, focusers, filter wheels, domes, and other observatory equipment through natural language.