"Satellite" matching MCP servers:

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 agents to query hyperlocal urban heat data for US locations, including street-level heatmaps, environmental parameters, satellite/street-view segmentation, and heat intelligence reports.

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 query Earth observation data, satellite imagery, active fires, and weather via natural language, returning interactive maps and briefs.

Enables retrieval of CelesTrak satellite pass predictions, NOAA space weather Kp observations and alerts, and conversion of ICAO NOTAM Q-line notices into GeoJSON bounding envelopes through MCP tools.

Provides access to SkyFi's satellite imagery API for searching, ordering, tasking, monitoring, and geographic operations through natural language.

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 geospatial operations such as geocoding, routing, map visualization, satellite imagery, and weather data through a unified MCP interface, making Earth data accessible to non-programmers.