"An email management MCP server" 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.

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.

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 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 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 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.

Enables LLMs and AI agents to interact with AFSIM through standardized MCP tools for scenario management, entity/component control, simulation execution, and results analysis.

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 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.

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.

Model Context Protocol server for pyCycle/OpenMDAO engine-cycle workflows, enabling lifecycle management, variable inspection, execution, sweeps, and integration with CPACS aircraft analysis pipelines.

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.

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.

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 control and automate Abaqus/CAE simulations via MCP, including model query, job management, ODB inspection, KPI extraction, capsule tracking, physics contract validation, report generation, and viewport capture. It also supports noGUI batch mode, dual transport, and integration with Codex/Claude clients.

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.

Enables interaction with SU2 CFD solver for session lifecycle management, config editing, solver execution, and results inspection, with optional CPACS integration for aircraft analysis.

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

Enables AI agents to interact with an ArduPilot vehicle in real-time via MAVLink, including reading state, inspecting and changing parameters, switching flight modes, diagnosing arming failures, and gated arming/disarming.

Enables checking US airports for ground stops, Ground Delay Programs, delays, and closures, while listing all active national airspace events and reading the Command Center's operations plan and full ATCSCC advisory text. It runs over stdio or Streamable HTTP and also decodes FAA event types, traffic-management terms, ARTCC codes, and identifier formats.

An MCP server that equips LLM clients with authoritative astrodynamics tools including TLE/SGP4 propagation, Lambert solving, ground-station access, time-scale and coordinate-frame conversions, and more.

An MCP server that lets an LLM operate an amateur radio shack: query live APRS traffic, predict satellite passes, schedule SDR captures, and monitor FT8/WSPR band activity.