Tomorrow.io MCP. Know the weather before you need to know it.
Tomorrow.io brings hyper-local weather intelligence directly into your AI client. It gives your agent minute-by-minute forecasts, current atmospheric data, and air quality reports for any location on Earth. Whether you're running complex supply chain models or planning an outdoor event, this MCP provides the precise environmental context needed to make critical, real-time decisions.
Give Claude and any AI agent real-world access
Retrieve immediate readings including temperature, humidity, and wind speed for a specific geographic area.
Access detailed forecasts with customizable time intervals, letting you plan minute-by-minute or day-by-day.
Monitor local air quality and pollution indices to assess safety levels for outdoor operations.
Fetch recent weather records, letting you analyze environmental trends over the last 24 hours or more.
List all current severe weather alerts and warnings issued for a specified region.
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What AI agents can do with Tomorrow.io: 5 Tools Available
Use these five specific tools to access everything from current temperature readings to long-term pollution analysis through your AI agent.
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 Air Quality
Retrieves specific air pollution measurements and indices for a given location.
List Weather Alerts
Checks and provides a list of all active severe weather warnings in an area.
Get Weather Forecast
Generates detailed future weather reports for any location over customizable...
Get Recent History
Pulls back a record of past weather conditions to help analyze long-term...
Get Realtime Weather
Provides immediate, current readings for temperature, humidity, and wind speed at a...
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.
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Managed infra
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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 Manual Headache of Environmental Planning
Right now, if your team needs to plan a multi-day outdoor event or manage cross-state deliveries, someone has to manually check three different websites. You're opening the general forecast site for wind speed; then you jump over to a separate air quality tracker for pollution levels; and finally, you have to consult a third page just to see if there are active severe weather advisories. Copying and pasting all this data into a single spreadsheet is tedious, slow, and prone to outdated information.
With this MCP, your agent handles the coordination. You ask it one question, like 'Should we proceed with the event?', and it instantly runs multiple checks—the current temperature via `get_realtime_weather`, pollution levels from `get_air_quality`, and any active warnings using `list_weather_alerts`. It synthesizes all that complex data into a single, actionable answer.
Tomorrow.io Gives You Predictive Environmental Data
Before this, predicting resource needs for farming meant looking at generic regional averages and hoping nothing unexpected happened in your specific field. Analyzing pollution risks required waiting until multiple agencies published reports—often hours apart.
Now, you can run `get_weather_forecast` on a hyper-local basis that matches your farm's coordinates. It's not just a general idea of rain; it tells you *when* and *how much*. Your decisions are guided by specific data points, not educated guesses.
What Tomorrow.io MCP does for your AI
Need to base a decision on what the weather will be? This connection gives your agent access to detailed atmospheric data and forecasts for any spot. It pulls in everything from current temperature and humidity readings to pollution levels and active warnings, all without you opening another browser tab or running a separate app.
You can ask your agent to check historical patterns over the last day or audit future conditions with custom time steps. When connected through Vinkius, your AI client acts like an instant meteorological consultant, feeding precise environmental data directly into your workflow so you never guess on logistics or safety again.
019d8490-0882-72d2-9bec-4f0b72c35677 How to set up Tomorrow.io MCP
The bottom line is you tell your AI client what information you need, and it handles all the API calls to get accurate weather data back.
Subscribe to this MCP on Vinkius and enter your Tomorrow.io API Key.
Your AI client connects, making the environmental data available as an accessible toolset.
You prompt your agent with a request (e.g., 'What will the air quality be in San Francisco tomorrow?') and it executes the necessary function.
Who uses Tomorrow.io MCP
Anyone whose daily operations depend on knowing the environment—from shipping cargo across state lines to planning large outdoor events. This MCP is for professionals who can't afford a single wrong call because of bad weather data.
Using get_weather_forecast, they adjust delivery routes and scheduling the moment rain or high winds are predicted, avoiding costly delays.
They analyze historical trends using get_recent_history to determine optimal times for irrigation cycles or harvesting crops.
Before a festival, they check list_weather_alerts and use the current conditions data to prepare backup safety plans for sudden storms.
Benefits of connecting Tomorrow.io MCP
Eliminate guesswork on field operations. Instead of relying on general forecasts, using get_realtime_weather gives your agent immediate data like wind speed and humidity for instant operational checks.
Plan with precision. Need to account for changing conditions? The ability to use get_weather_forecast lets you plan logistics hour by hour or day by day, improving route reliability dramatically.
Prioritize safety instantly. Before an event starts, running list_weather_alerts ensures your agent knows if there are active warnings—like flash flood or high wind advisories—that require immediate action.
Optimize resource use. Agronomists can check historical trends using get_recent_history. This data helps them determine if the last week's rainfall was unusually low, guiding better irrigation plans.
Monitor public health risks. By calling get_air_quality, your agent automatically checks for pollution spikes (like high PM2.5) and can advise users to postpone outdoor activities when air safety is compromised.
Tomorrow.io MCP use cases
Rerouting a Fleet During Storms
A logistics manager needs to move goods through the Midwest, but a storm track develops. They ask their agent for the forecast and use get_weather_forecast to identify areas hit by severe weather, rerouting the entire fleet before any delays happen.
Planning an Outdoor Festival
An event organizer needs to know if a weekend outdoor market is safe. They run list_weather_alerts and check the air quality via get_air_quality, ensuring they have enough time to secure vendors against predicted wind gusts.
Diagnosing Crop Stress
An agronomist notices wilting crops. They use get_recent_history and combine it with the real-time data from get_realtime_weather to determine if a recent heat spike or change in humidity was responsible for the poor yield.
Emergency Preparedness Check
A facility manager needs to know if they can operate safely after a local incident. They check get_realtime_weather for current wind speeds and use get_air_quality to confirm that pollution levels are safe for personnel reentry.
Tomorrow.io MCP tradeoffs
What to watch out for, and the recommended way to handle each one.
Assuming generalized data is enough
Asking a general-purpose agent, 'What's the weather like in Texas?' The result will be too broad and useless for specific operational planning.
Always specify location granularity. Use get_realtime_weather or get_weather_forecast and include coordinates or a very specific ZIP code to get hyper-local data.
Only checking the current moment
Using only the current readings, like get_realtime_weather, when planning an activity for tomorrow. This gives you zero predictive power.
If you're planning ahead, always use get_weather_forecast. It provides customizable time steps so you can audit conditions far into your future timeline.
Ignoring environmental context
Asking for a logistics route without considering local risks. This might lead to sending drivers through an area currently under a high-wind alert.
Check list_weather_alerts first. If alerts are active, do not proceed with planning until the agent confirms the warnings have cleared.
When to use Tomorrow.io MCP
Use this MCP when your operational decisions hinge on dynamic environmental conditions: logistics routing, construction scheduling, outdoor event safety, or agricultural timing. You need predictive power and current atmospheric readings. Don't use it if you just need general knowledge (e.g., 'What is the capital of France?'). For basic data visualization based on fixed metrics (like reading a static database table), stick to specialized data connectors. If your concern is purely historical, you can limit yourself to get_recent_history, but remember that for actionable planning, you need the combination of real-time and forecast tools.
Frequently asked questions about Tomorrow.io MCP
How accurate is the Tomorrow.io MCP for severe weather alerts? +
The list_weather_alerts tool provides access to official and real-time warnings issued for specific geographic areas, ensuring you stay updated on dangerous conditions like tornados or floods.
Can I use Tomorrow.io to check historical weather data? +
Yes. The get_recent_history tool lets you retrieve past environmental records for the last 24 hours, which is crucial for understanding long-term patterns and diagnosing problems.
Does Tomorrow.io provide air quality data for multiple pollutants? +
The get_air_quality tool monitors overall pollution levels and indices (like AQI) based on key components such as PM2.5, helping you determine if the environment is safe for people or equipment.
What if I need a forecast for next week using Tomorrow.io? +
While get_weather_forecast provides detailed predictions with customizable steps, always check the service documentation regarding the maximum lead time available for hyper-local data.
Is the real-time weather data reliable enough for construction planning? +
The get_realtime_weather tool gives immediate readings on temperature and wind speed, which are critical inputs for safety assessments in construction and engineering fields.