How to Use the Tomorrow.io Extended MCP in Cursor

Q: Can I get recent weather history using Tomorrow.io Extended in Cursor?

Yes, use getrecenthistory to pull data points into your project's context. This is useful when you need to validate a function against known past measurements.

Q: Does Tomorrow.io Extended provide air quality data for Cursor?

The getairquality tool pulls the current AQI and supporting metrics, which your agent can then use to write validation checks in your code base. It's perfect for environmental monitoring apps.

Q: Is Tomorrow.io Extended reliable for predicting weather with Cursor?

The getweatherforecast tool uses established prediction models, allowing you to build robust forecasting logic directly into your application code. You get the predictions ready to run.

Write code using live weather data with Cursor.

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Connect Tomorrow.io Extended MCP to Cursor

Create your Vinkius account to connect Tomorrow.io Extended to Cursor and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Tomorrow.io Extended with Cursor

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Claude

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Inject real-time conditions into your scripts.

Working on a script that needs to display current local weather? Call `get_realtime_weather` directly within the AI agent context. The response feeds live temperature, wind, and humidity data straight back into the code block. You'll write working functions that use real API responses—no more using mock stubs or dummy data for testing.

Build alerts based on severe weather events.

Need to write a monitoring script? Use `list_weather_alerts` to check for active warnings. The agent can parse this list and generate conditional logic (if/else statements) in your code. This lets you build immediate, functional checks that trigger based on actual weather advisories.

Compare current readings against history.

Writing a performance script for environmental data? Combine `get_air_quality` with `get_recent_history`. The agent handles the comparison, letting you write logic that measures air quality trends over weeks. You can build tools that flag when current AQI readings deviate significantly from historical norms.

Setup guide

Set up Tomorrow.io Extended MCP in Cursor

Prerequisites

Cursor installed (macOS, Windows, or Linux)
Active Vinkius subscription with a valid endpoint token

1

Open MCP Settings

Go to Cursor Settings → MCP or open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and search for "MCP: Add Server".
2

Add the Tomorrow.io Extended MCP

Cursor will create or open .cursor/mcp.json in your project root. Paste the JSON snippet on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Enable Agent mode

Open Composer (Cmd+I / Ctrl+I) and switch to Agent mode using the dropdown at the top. MCP tools are only available in Agent mode.
4

Verify the connection

Ask Cursor something like "List my recent Tomorrow.io Extended transactions." If the MCP tools are loaded correctly, Cursor will call the Tomorrow.io Extended tools automatically. You can also check Settings → MCP for a green status indicator.

.cursor/mcp.json

{
  "mcpServers": {
    "tomorrowio-extended-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

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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Common questions about Tomorrow.io Extended MCP in Cursor

When you're coding, simply ask the agent to generate code that calls `get_weather_forecast`. It will write out the function structure and populate it with predicted temperature ranges for future dates.

Yes, use `get_recent_history` to pull data points into your project's context. This is useful when you need to validate a function against known past measurements.

The `get_air_quality` tool pulls the current AQI and supporting metrics, which your agent can then use to write validation checks in your code base. It's perfect for environmental monitoring apps.

The `get_weather_forecast` tool uses established prediction models, allowing you to build robust forecasting logic directly into your application code. You get the predictions ready to run.

This server deals with environmental measurements: temperature, atmospheric pressure, wind speed, air quality index (AQI), and historical weather metrics. The code you write uses this structured data.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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