# Tomorrow.io MCP

> Tomorrow.io provides access to hyperlocal weather intelligence, letting your AI client pull real-time conditions, detailed forecasts, and decades of historical climate data. Plan complex logistics, analyze insurance claims, or build advanced dashboards using precise weather information for any global location.

## Overview
- **Category:** iot-hardware
- **Price:** Free
- **Tags:** weather-forecasting, hyperlocal-data, real-time-monitoring, air-quality, severe-weather-alerts, historical-weather

## Description

Need reliable weather data that goes way beyond a simple forecast? This MCP connects your agent to enterprise-grade meteorological intelligence. You can ask it for current conditions—like temperature and air quality—for any place on Earth. Planning a road trip? It figures out the expected weather along the entire route, not just the endpoints. Need to analyze climate change or process an insurance claim? The system pulls decades of historical data, allowing you to query specific fields over huge date ranges. For ongoing operations, it monitors active severe weather warnings and provides multi-resolution forecasts, giving you hourly predictions for wind and precipitation probability. This entire suite of capabilities is hosted on Vinkius, letting any MCP-compatible client use the full catalog without extra steps.

## Tools

### get_daily_forecast
This tool provides a simple daily weather forecast suitable for general travel and weekly planning.

### get_weather_events
It identifies active alerts, like storm warnings or heat advisories, that might affect a specific area right now.

### get_forecast
You get an extended weather prediction for up to 14 days, covering temperature, humidity, and wind probability.

### get_historical_weather
This tool retrieves observed daily or hourly data across a specified date range for deep analysis.

### get_hourly_forecast
It gives an hour-by-hour prediction, which is necessary when you need to plan activities within the next few days.

### list_locations
You check and manage a list of frequently monitored areas saved in your Tomorrow.io account.

### get_realtime_weather
This provides the immediate, current weather conditions for any location using city names or coordinates.

### get_recent_history
It retrieves actual observed weather data from the past 24 hours to verify very recent events.

### get_route_weather
You plan a trip by getting expected weather conditions for every waypoint along a multi-stop travel route.

### get_timeline
This advanced tool lets you build highly specific data queries, selecting exact metrics and time intervals for custom dashboards.

## Prompt Examples

**Prompt:** 
```
What's the weather like in Tokyo right now?
```

**Response:** 
```
Currently in Tokyo: 🌡️ 18.5°C, 💧 62% humidity, 💨 12 km/h NW wind, clear skies with 0% precipitation probability. UV index is 3 (moderate). Visibility is excellent at 16 km.
```

**Prompt:** 
```
Give me an hourly forecast for São Paulo for the next 12 hours.
```

**Response:** 
```
Hourly forecast for São Paulo: 14:00 — 27°C, 45% humidity, 8% rain chance | 15:00 — 28°C, 42%, 5% | 16:00 — 26°C, 55%, 25% | 17:00 — 24°C, 68%, 60% — thunderstorm likely | 18:00 — 22°C, 78%, 85% — heavy rain expected. I'd recommend carrying an umbrella after 4 PM.
```

**Prompt:** 
```
What was the weather like in London on January 15, 2025?
```

**Response:** 
```
Historical weather for London on January 15, 2025: High 7.2°C, Low 2.1°C, 89% humidity, 22 km/h SW wind, 4.8mm rainfall recorded, overcast skies throughout the day. Visibility was reduced to 8km due to light drizzle in the morning.
```

## Capabilities

### Check current conditions
You get immediate details like temperature, humidity, wind speed, and air quality for a specific location.

### Predict future weather patterns
You receive detailed forecasts—hourly or spanning up to two weeks—including chances of rain, pressure changes, and wind direction.

### Analyze historical climate data
You pull observed weather records dating back 20 years for deep research or verifying past events.

### Plan routes with predictive weather
You get a forecast that follows a multi-stop path, allowing you to plan logistics around expected conditions at every waypoint.

## Use Cases

### Verifying an insurance claim.
An adjuster needs to know if the wind speed exceeded 40 mph on a specific date last year. They connect their agent, ask it to use `get_historical_weather`, and get confirmed records for that exact metric and date range.

### Planning an outdoor festival.
The event organizer needs accurate timing. By using `get_hourly_forecast` days out, they can see when high wind probability is expected, allowing them to schedule vendor setup around the risk window.

### Coordinating a cross-country delivery.
The dispatch team uses this MCP with `get_route_weather`. The agent calculates weather conditions not just for Denver and Miami, but for every town between them, rerouting the driver proactively.

### Building an advanced climate dashboard.
A data scientist needs to compare precipitation probability across three different metrics (wind speed, humidity, UV index) over a 14-day period. They use `get_timeline` to pull all these specific fields at precise intervals.

## Benefits

- Instead of checking multiple tabs for current conditions, you simply ask your agent to use `get_realtime_weather` and get immediate data on temperature, humidity, and air quality in one go.
- Forecasting used to mean guessing. Now, using `get_hourly_forecast`, you can plan activities with high confidence because the system provides predictions for wind, pressure, and precipitation hour by hour.
- For insurance or research, waiting days for data is unacceptable. With this MCP, `get_historical_weather` lets you pull specific fields from up to 20 years of archived data instantly.
- Logistics planning changes entirely when your agent uses `get_route_weather`. You don't get weather for the start and end points; you get a forecast along the entire multi-waypoint path.
- If you need deep analytics, forget general reports. The `get_timeline` tool lets you build precise queries defining exactly which metrics and time steps are needed for your custom dashboards.

## How It Works

The bottom line is that you talk to your AI agent using plain English, and it handles all the complex API calls for precise weather answers.

1. Subscribe to this MCP and generate your API key through the Vinkius catalog.
2. Connect your agent—whether it's Claude, Cursor, or another client—using your credentials.
3. Ask natural language questions like 'What was the wind speed in Chicago on May 1st?' and receive structured weather data.

## Frequently Asked Questions

**How do I get the current weather using Tomorrow.io MCP?**
You use `get_realtime_weather`. You simply provide a location—like 'Paris' or coordinates—and the agent returns immediate details on temperature, wind, and air quality.

**Can I check historical data using Tomorrow.io MCP?**
Yes, you use `get_historical_weather`. You specify a date range and what fields you need—like rainfall or humidity—and the tool retrieves observed records from up to 20 years.

**What is the difference between get_forecast and get_hourly_forecast?**
The `get_forecast` gives a general prediction for days ahead. If you need detailed timing, like knowing if rain will hit at 3:00 PM or 4:00 PM, use `get_hourly_forecast`.

**Can I plan a route using Tomorrow.io MCP?**
You run the multi-stop path through `get_route_weather`. This tool ensures that the forecast is accurate for every single point along your planned journey, which is critical for logistics.

**How can I analyze specific metrics over time with Tomorrow.io MCP?**
Use the advanced `get_timeline` tool. It lets you dictate exactly which data points—like wind speed or UV index—and what intervals are necessary for your custom analytics.