"Satellite" matching MCP servers:

A Model Context Protocol (MCP) server for searching STAC catalogs, downloading satellite bands, and creating composites via 21 tools.

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.

Enables interactive access to JAXA's satellite observation data (precipitation, land surface temperature, NDVI, elevation, soil moisture) via Claude, providing tools for point time series, dataset information, and area image generation.

Enables AI coding agents to score any geographic coordinate for ecological and agricultural land suitability by analyzing satellite and climate data, returning a weighted score with per-metric breakdowns for vegetation, water, terrain, and more.

Enables AI agents to autonomously discover, stream, and compute satellite analytics from free government Earth observation archives. Provides tools for STAC search, spectral indices, elevation profiles, SAR water detection, and sandboxed geospatial scripting.

A Python MCP server that provides unified access to satellite and geospatial data through natural language queries, with automatic place name geocoding and support for raster, vector, and Zarr formats.

Provides tools to search, download, and manage satellite imagery from all Copernicus Sentinel missions via the Copernicus Data Space ecosystem. It enables advanced geospatial queries, temporal coverage analysis, and automated data management for Earth observation tasks.

Enables discovery, analysis, and explanation of open satellite data through MCP, with support for STAC catalogs and NASA GIBS.

Enables retrieval of satellite vegetation statistics (NDVI) and searches of Sentinel-2 scene catalogs, returning results as JSON.

Enables searching and querying oceanographic data from any ERDDAP server — catalog lookup, dataset metadata, tabular tabledap queries and gridded satellite SST fields — keyless and read-only. It works out of the box against curated or arbitrary ERDDAP endpoints with caching and result caps to keep queries safe.

Enables querying current and historical relative water levels for 518 lakes, seas, and reservoirs worldwide from satellite radar altimetry, with search by name, country, or continent.

Enables MCP clients to access Google Earth Engine's satellite imagery and geospatial analysis capabilities. Provides tools for vegetation analysis, crop classification, disaster monitoring, and interactive map creation using petabytes of satellite data.

Enables searching NASA GIBS' 1,300+ satellite imagery layers, retrieving detailed layer metadata, and generating tile URLs for any date and location, covering datasets like true-color mosaics, thermal anomalies, and night lights.

Enables querying NOAA CoastWatch satellite and model ocean data from ERDDAP servers, including sea surface temperature, chlorophyll-a, winds, currents, and NDBC buoy observations.

A standalone Model Context Protocol server that lets AI clients search satellite scenes, fetch weather and climate series, query geographic layers, and compute vegetation indices and gradual-pattern analyses over environmental time series, returning structured results with source and limit metadata. It exposes 16 tools over stdio, streamable HTTP or legacy SSE and runs its own data retrieval and calculations.

Enables searching Microsoft Planetary Computer's STAC catalogue by area and date across open satellite and environmental collections, returning item IDs, footprints, dates, cloud cover, and per-band asset URLs.

A feature-rich NASA data query tool that supports various NASA API services including astronomy pictures, Mars rover photos, Earth satellite images, near-Earth objects data, and space weather information through natural language queries.

An MCP server providing AI agents with access to satellite imagery, geospatial intelligence, and billing management through the SkyFi platform.

Production-ready satellite imagery analysis server that enables natural language queries for Earth observation data, including land cover classification, vegetation monitoring, water detection, change detection, and automated environmental reporting.

Enables satellite imagery analysis through Google Earth Engine, allowing users to search datasets, calculate vegetation indices like NDVI, filter collections by location and date, and export imagery to cloud storage. Supports major satellite datasets including Sentinel-2, Landsat, and MODIS for applications like agriculture monitoring and deforestation tracking.