"Enhance AI Coding Accuracy in Windsurf Code Editor by Codeium" matching MCP servers:

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

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

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.

Enables building and flying rockets in Kerbal Space Program 1.x via MCP, providing editor, flight control, and real-time telemetry tools without requiring visual input.

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.

Gives AI assistants read-only access to public astronomy archives (TNS, SIMBAD, VSX, Gaia, TESS, ZTF, Rubin and others) so a sky position or object can be checked in seconds for whether it is already known. It returns compact JSON verdicts with evidence, failed sources, image links, and tonight's observable unclassified transients.

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

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.

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

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.

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.

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.

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.

Vedaksha MCP Server Astronomical ephemeris and Vedic astrology computation for AI agents via the Model Context Protocol.

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.