Tomorrow.io Plus MCP. Know exactly what the weather will do next.

You connect this server to your AI agent when you need reliable, deep weather intelligence straight from the source. This isn't just some basic API call; it gives your agent structured tools for making calls based on accurate atmospheric data. You gotta know what’s going down with the weather—right now, next week, or even last month.

When you need to check current conditions, your agent runs get_realtime_weather to pull the latest reading for any spot. This tells you immediate details like temperature, wind speed, and visibility exactly where you point it. For planning ahead, you can get predictions using get_forecast_weather, which pulls structured data covering both hourly changes and full day-by-day forecasts.

You'll know what to expect for your operations.

Building graphs over time requires more than a simple forecast. If you need deep metrics—say, tracking temperature swings or rain intensity over a specific period—you use get_timelines. For complex areas that aren’t just points on a map, like following the path of a river or a factory footprint, you send geometry data to post_timelines to pull those detailed weather metrics.

You can also see what happened in the last twenty-four hours by calling get_recent_history_weather. When visualizing this stuff on a map for your users, your agent retrieves specific map image pieces, or tiles, using get_map_tile, letting you overlay current or predicted weather layers right onto existing geospatial visuals.

For risk management, the server gives you serious control. You can check for official, pre-defined warnings by calling list_alerts; this flags high-priority weather dangers relevant to your monitored locations. If you need to know about specific kinds of bad weather—like hail or fog—you use list_events to pull those localized event types based on a category.

You don't have to guess what kind of warnings are available; calling list_insights shows all the pre-defined categories you can filter data and alerts by. To keep your operations consistent, your agent uses list_locations to manage and retrieve a list of every geographical spot you’ve saved in the account.

It's a whole system that coordinates everything. You run these tools together—you get immediate conditions from get_realtime_weather, then use get_forecast_weather for planning, pull historical data with get_recent_history_weather, map it all out with get_map_tile, and finally check the risk level using list_alerts. You'll have a full picture of what’s going down.

The whole thing gives your agent access to granular detail, making sure you never run blind on weather conditions again.