"Notes or documentation related to 'rag'" matching MCP servers:

Enables AI agents to access spaceflight news data through the Pipeworx MCP gateway, allowing natural language queries for space-related articles and updates.

MCP server for designing drones and related physical systems through natural language in Spanish, with deterministic calculation and simulation.

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.

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.

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.

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.

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

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.

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.

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

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 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.

This MCP server enables AI agents to control kOS computers in Kerbal Space Program, providing tools for scripting, telemetry, and simulation management via telnet and file system integration.

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.

Viznoir empowers AI agents to directly analyze and visualize complex 3D scientific and engineering data in cinematic resolution using a fully headless VTK engine. It enables LLMs to seamlessly execute advanced physical analysis, 3D rendering, and generate publication-ready animations purely through natural language commands.

Unified SPEDAS-oriented MCP server for Claude Code and Codex agents, providing tools to discover and fetch heliophysics and planetary science data from CDAWeb, NASA PDS, and SPICE kernels.

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.