"Connecting to SEC EDGAR MCP using Bedrock Models" 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.

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.

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.

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.

Enables MCP clients to search, read, and cite the EASA Easy Access Rules with exact rule references, metadata, and linked AMC/GM. It covers aircrew, air operations, SERA, sailplanes, balloons, continuing airworthiness, basic regulation, drones, and aerodromes, returning ranked results and full rule text.

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.

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.

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 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.

Enables AI agents to identify and diagnose ArduPilot flight controllers over MAVLink, reading status, parameters, backups and diffs, and running guided calibrations. It is read-only by default, with human-approved, read-back-verified parameter changes and identity-checked backups gated behind explicit flags.

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.

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.

Official bounded, read-only access to live community-powered aircraft positions and aggregate ADSBiq network statistics.

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 users to query live local ADS-B flight data from their own receiver, listing aircraft overhead or near a point and finding aircraft by callsign, ICAO hex code, or registration.

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.

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.

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 MCP clients to look up tracked satellites and debris, analyze debris fields and constellations, find predicted close approaches, and retrieve NOAA space-weather scales, alerts, and plain-English impacts.

Enables MCP clients to retrieve live worldwide launch schedules with countdowns, Starship status, satellite and ISS pass predictions for any location, and visible Starlink train forecasts, with cited source URLs and fetch timestamps.