"Cloud Foundry" matching MCP servers:

Provides hosted, read-only Google Maps tools for MCP clients, enabling place search, full place details, reviews, photos, posts, and contributor history without a Google Cloud project or billing.

Finds the clearest Sentinel-2, Landsat, Sentinel-1, or NAIP scene for any location and time, ranked by area coverage, cloud cover, and date, with previews and band download links.

Adapts the HeFeng QWeather MCP server for ModelScope cloud hosting, allowing weather queries through stdio or HTTP with a default stdio entry.

Enables voice assistants and any MCP client to ask whether the northern lights are visible right now or tonight at a given place or coordinates, returning a spoken verdict with the chance they'll be bright enough for the eye or a camera, along with darkness, cloud cover, and where to look. It also explains current space weather, with structured numbers behind each sentence.

Provides Google Maps functionality through Cloud Run, enabling route calculation, traffic analysis, route comparison, and trip cost estimation with rate-limited public access.

Enables AI assistants to authenticate against a cloud geospatial analysis platform, search and inspect its datasets, render them as maps, and compute statistics over specified regions. It exposes these capabilities as MCP tools that can be dropped into any Next.js project via a route-based adapter.

Enables querying Sentinel-1/2, Landsat Collection 2, NAIP, and Copernicus DEM imagery by area and date, returning item IDs, footprints, cloud cover, and cloud-optimized GeoTIFF URLs.

Minimal MCP server exposing tools for kitesurfing forecasts (wind and waves via Open-Meteo) and tide predictions (via NOAA CO-OPS).

A local GeoGuessr-for-real-life: reads EXIF GPS and reasons over visual clues using a local uncensored vision-language model + a reasoning model — no cloud, no API keys, nothing uploaded.

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.

Enables users to ask an MCP client whether golden-hour sunrise or sunset light will be visible on Chinese snow mountains from a given viewpoint, returning golden-hour time windows, a 0-100 visibility score, and weather factors like cloud cover, humidity, and wind. It also supports searching peaks and viewpoints by name and finding nearby visible peaks by latitude and longitude for the next 1-7 days.

Enables AI agents to autonomously discover, stream, and compute satellite analytics from free government Earth-observation catalogs such as Sentinel-2, Landsat, and Copernicus DEM, with zero API keys or configuration. It supports place-name geocoding, STAC scene search, cloud-native COG streaming for spectral indices, elevation profiles, SAR flood detection, and sandboxed custom geospatial scripts.

Enables any MCP-capable agent to read and write a local personal timeline — GPS tracks, photos, workouts, health metrics, and stays — through seven indexed tools for monthly timelines, cross-modal lookups around a moment, geo-track retrieval, atlas exports, and idempotent JSONL ingestion. All data stays in a single on-device SQLite file, with no arbitrary SQL and no cloud.