Tomorrow.io MCP. Know the weather today, tomorrow, or 20 years ago.
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.
Give Claude and any AI agent real-world access
You get immediate details like temperature, humidity, wind speed, and air quality for a specific location.
You receive detailed forecasts—hourly or spanning up to two weeks—including chances of rain, pressure changes, and wind direction.
You pull observed weather records dating back 20 years for deep research or verifying past events.
You get a forecast that follows a multi-stop path, allowing you to plan logistics around expected conditions at every waypoint.
Ask an AI about this
Waiting for input…
What AI agents can do with Tomorrow.io: 10 Tools for Weather Data Processing
These tools allow you to retrieve everything from immediate current conditions to complex, multi-decade climate records.
Make your AI actually useful.
Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.
Start using Tomorrow.io MCPGet 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...
Get Forecast
You get an extended weather prediction for up to 14 days, covering temperature...
Get Historical Weather
This tool retrieves observed daily or hourly data across a specified date range for...
Get Hourly Forecast
It gives an hour-by-hour prediction, which is necessary when you need to plan...
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...
Get Route Weather
You plan a trip by getting expected weather conditions for every waypoint along a...
Get Timeline
This advanced tool lets you build highly specific data queries, selecting exact...
Security and governance baked right in.
Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.
Choose How to Get Started
Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.
Build Your Own
Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.
- Import from OpenAPI, Swagger, or YAML specs
- Create Agent Skills with progressive disclosure
- Deploy to edge with MCPFusion framework
- Built in DLP, auth, and compliance on each call
- Real time usage dashboard and cost metering
- Publish to catalog or keep private
Make Your AI Do More
Start with Tomorrow.io, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.
- Use this MCP plus 5,200+ others, all in one place
- Add new capabilities to your AI anytime you want
- Connections are secured and governed automatically
- Track usage and costs across all your servers
- Works with Claude, ChatGPT, Cursor, and more
- New servers added to the catalog weekly
Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Tomorrow.io. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
VINKIUS CLOUD
Cloud Hosted
Managed infra
V8 Isolated
Sandboxed per request
Zero-Trust Proxy
No stored credentials
DLP Enforced
Policy on each call
GDPR Compliant
EU data residency
Token Compression
~60% cost reduction
The headache of manual weather data collection
Today, checking complex weather patterns means jumping between multiple sites: one for current conditions, another for a 14-day outlook, and finally opening spreadsheets to manually input historical ranges. You spend time cross-referencing wind speeds from different quarters just to build a basic dashboard.
With this MCP, you tell your agent what data you need—for example, 'I need the temperature and precipitation probability for every hour on my route next week.' The system handles all that complexity, giving you one clean, accurate data set ready for analysis.
Get actionable insights using get_route_weather
Before this, planning a delivery meant looking at the weather only in the start city and the end city. You'd plan based on an optimistic forecast that completely ignored potential storms or high winds along the middle segments of the journey.
Now, when you ask the agent to use `get_route_weather`, it calculates conditions for every single waypoint between your origin and destination. That means your logistics plans are built around actual expected environmental risk, not just city averages.
What Tomorrow.io MCP does for your AI
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.
019d848f-d9de-70df-b111-385cd7ab4d15 How to set up Tomorrow.io MCP
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.
Subscribe to this MCP and generate your API key through the Vinkius catalog.
Connect your agent—whether it's Claude, Cursor, or another client—using your credentials.
Ask natural language questions like 'What was the wind speed in Chicago on May 1st?' and receive structured weather data.
Who uses Tomorrow.io MCP
This is for operations teams who can't afford delays due to bad forecasting. It’s needed by insurance adjusters verifying claims against old data and researchers tracking climate changes over decades.
You use this MCP to plan multi-stop delivery routes, ensuring the AI checks for expected severe weather along every segment.
You query historical archives using this MCP to verify if recorded weather events (like wind or rainfall) match claim dates and locations.
You pull custom timelines, specifying exactly which data fields you need over specific date ranges for academic modeling.
Benefits of connecting Tomorrow.io MCP
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.
Tomorrow.io MCP 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.
Tomorrow.io MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Assuming general forecasts are enough.
Just asking for 'next week' and getting a simple daily summary that ignores critical changes like wind shear or localized storms.
For detailed planning, use get_hourly_forecast to pinpoint high-risk hours. If you need multi-stop coverage, always run the query through get_route_weather.
Trying to verify a recent event by guessing.
Manually checking news reports for 'what was the weather like yesterday?' and getting vague descriptions of conditions.
Use get_recent_history. This tool pulls actual observed conditions—including temperature, wind, and precipitation—from the last 24 hours.
Limiting analysis to current data only.
Only checking today's forecast when you actually need to compare this year's rainfall against average historical records from the past decade.
For long-term research, use get_historical_weather or get_timeline. These tools give you access to decades of archived data.
When to use Tomorrow.io MCP
Use this MCP if your core problem involves predicting, verifying, or calculating based on weather conditions—whether that's for logistics (route planning), risk assessment (insurance/actuarial), or scientific modeling (climate research). If you need to know the temperature in Tokyo right now, use get_realtime_weather. If you just want a general idea of next Saturday, use get_daily_forecast. However, don't use this if your data needs are purely geographical and unrelated to weather patterns; for example, predicting traffic volume is outside its scope. Furthermore, if you only need the average temperature over 10 years without specific wind speed metrics, consider using a dedicated statistical database instead of relying solely on get_historical_weather. Always match your query specificity (e.g., hourly vs. daily) to the required tool.
Frequently asked questions about Tomorrow.io MCP
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.