How to Use the Tomorrow.io Plus MCP in VS Code Copilot

Q: Is Tomorrow.io Plus reliable for complex location data?

Yeah, absolutely. The posttimelines() tool supports GeoJSON geometries, meaning you can pass weather requests for custom-shaped regions that simple coordinates won't cover.

Q: What about Tomorrow.io Plus and VS Code Copilot when onboarding new devs?

You commit the MCP configuration to the project root (.vscode/mcp.json). Every developer instantly gets access to all the weather tools without manual setup.

Q: Can Tomorrow.io Plus list available data categories?

Yes, you can call listinsights() to see all pre-defined or custom insight categories, helping your team scope what kind of weather events they need data for.

Get team-wide access to hyper-local weather data via VS Code Copilot's MCP Server integration.

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Connect Tomorrow.io Plus MCP to VS Code Copilot

Create your Vinkius account to connect Tomorrow.io Plus to VS Code Copilot 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 Plus with VS Code Copilot

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Check real-time and historical conditions

The engineering team can use `get_realtime_weather()` to verify current location conditions while coding. If you need to back-check data, the Copilot Chat agent calls `get_recent_history_weather()` for records from the last day. This means your entire team uses a single, consistent source of truth for weather context.

Manage alerts and specific events

Before committing code that relies on external data, run `list_alerts()` to see if any active weather warnings exist. You can also call `list_events()` to verify categories of severe weather for a region. This helps prevent bugs caused by unpredicted environmental changes.

Retrieve complex forecast timelines

For planning features, the team uses `get_forecast_weather()` to pull out hourly or daily predictions. If you need detailed metrics like precipitation intensity across a large area, use `post_timelines()` for GeoJSON geometries. The whole process is shared via the repo's MCP configuration.

Setup guide

Set up Tomorrow.io Plus MCP in VS Code Copilot

Prerequisites

VS Code 1.99 or later with GitHub Copilot extension
Active Vinkius subscription with a valid endpoint token

1

Open MCP configuration

Open the Command Palette (Cmd+Shift+P / Ctrl+Shift+P) and run "MCP: Add Server". Select HTTP (Streamable) as the server type. VS Code will create .vscode/mcp.json in your workspace.
2

Add the Tomorrow.io Plus MCP

Paste the JSON snippet shown on the right into your .vscode/mcp.json. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Switch to Agent mode

Open Copilot Chat (Cmd+Shift+I / Ctrl+Shift+I) and switch to Agent mode using the dropdown. MCP tools are only available in Agent mode — they do not appear in Edit or Ask modes.
4

Verify the connection

In the Copilot Chat input, type # to list available tools. You should see the Tomorrow.io Plus tools listed. Try asking: "List my recent Tomorrow.io Plus transactions" and Copilot will invoke them automatically.

.vscode/mcp.json

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

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Common questions about Tomorrow.io Plus MCP in VS Code Copilot

You simply ask your AI client in Copilot Chat to pull the needed weather information, specifying which tool it should use (e.g., `get_forecast_weather()`). The team configuration handles the rest.

Yeah, absolutely. The `post_timelines()` tool supports GeoJSON geometries, meaning you can pass weather requests for custom-shaped regions that simple coordinates won't cover.

You commit the MCP configuration to the project root (`.vscode/mcp.json`). Every developer instantly gets access to all the weather tools without manual setup.

Yes, you can call `list_insights()` to see all pre-defined or custom insight categories, helping your team scope what kind of weather events they need data for.

It handles core weather metrics like temperature, precipitation intensity, and comprehensive forecasts across various time ranges.

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