Stormglass MCP for AI. Predict environmental conditions anywhere on Earth.

This server connects your AI agent directly to professional-grade environmental data for any spot on Earth. It fetches high-resolution forecasts covering weather, tide levels, marine life metrics, and even celestial events—all in one place. You'll build predictive models for everything from complex maritime logistics to deep climate research.

When you use this server, your agent accesses five specialized tools that pull real-time or forecasted data across multiple critical domains:

Weather Forecasting: You can get live weather data using get_weather_point. This tool gives you wind speed and wave height measurements for a specified coordinate, plus the air temperature. If you're planning an offshore survey, you check these points to ensure conditions are safe. The agent gathers this information so your client knows exactly what it's dealing with.

Tide & Sea Level Analysis: For any coastal operation, knowing the water level is everything. You use get_tide_extremes_point to calculate the absolute maximum and minimum high and low tides expected at a location over time. If you need to know when the docks will be completely submerged or highest, this is your tool.

Furthermore, if you're monitoring continuous changes—say, tracking coastal erosion or river flow over hours—you run get_tide_sea_level_point. This function returns detailed sea level measurements at set time intervals, letting you see how the water height shifts minute by minute.

Marine Ecology Monitoring: Need to know what's actually floating out there? You use get_bio_point to pull biological data. It retrieves current marine metrics like oxygen levels or chlorophyll concentrations right at a specific point. This is vital for scientific analysis, letting you track the health of an ecosystem without having to deploy physical sensors yourself.

Astronomy & Celestial Events: If your operation depends on the sun or moon—like solar panel deployment or deep-sea photography—you use get_astronomy_point. It fetches precise data points for sunrise, sunset, and all the moon phases. You'll get accurate times for when the celestial bodies will be above the horizon at any coordinate.

Putting it Together: The server lets your agent analyze sea levels across specific time intervals using get_tide_sea_level_point, while simultaneously checking predicted extreme tides with get_tide_extremes_point. You can combine these water movement metrics with wind and wave data from get_weather_point to forecast the exact operational window for a vessel. For climate modeling, you pair biological readings—like oxygen levels via get_bio_point—with historical weather patterns fetched through multiple points in time.

Your agent doesn't just get single numbers; it pulls coordinated data. You can cross-reference the sunset times from get_astronomy_point with expected wave heights from get_weather_point to plan a deep-sea recovery mission that must happen after dark but before the tide drops too low. If you need to model how changes in chlorophyll concentration correlate with sea level fluctuations, you pull both datasets using their respective tools and run your prediction.

The ability to query both upcoming predictions and historical data points across all these metrics—all linked by specific time stamps—means you never have to leave this single source for global environmental information.