How to Use the Tomorrow.io Plus MCP in Google ADK

Q: How does Google ADK handle weather alerts with Tomorrow.io Plus?

Your LlmAgent calls listalerts to get an immediate list of active warnings. Since you're using BigQuery, this data can be mapped directly onto existing operational datasets for faster analysis.

Q: Can I track historical weather trends with Tomorrow.io Plus and Google ADK?

Absolutely. The getrecenthistoryweather tool retrieves the last 24 hours of data, which you can then use to train or validate models running on your cloud infrastructure.

Q: What locations are available with Tomorrow.io Plus and Google ADK?

The listlocations tool shows all pre-defined account locations. If they aren't listed, you can use the agent to query for data using coordinates via other tools.

Q: What is required to predict future weather conditions?

You need to call getforecastweather. This tool provides hourly and daily forecasts. Your Google ADK agent then uses this structured forecast data for predictive modeling within the cloud environment.

Analyze enterprise weather patterns using Google ADK with Tomorrow.io Plus.

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Connect Tomorrow.io Plus MCP to Google ADK

Create your Vinkius account to connect Tomorrow.io Plus to Google ADK 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 Google ADK

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List All Weather Alerts in the MCP Server

The `list_alerts` tool allows your Google agent to pull all active weather warnings across multiple locations. This is crucial for enterprise risk management, immediately flagging potential shutdowns or delays. It gives you a centralized view of danger zones. You don't have to check dozens of sources; the MCP Server aggregates and presents every relevant alert through one tool call.

Manage Weather Events with Google ADK

The `list_events` tool retrieves detailed weather events based on specific insight categories. If you're tracking hurricanes or flash floods, this is how your agent finds the records. It lets you filter by category and location simultaneously. This means you can build highly focused pipelines in Vertex AI that only process relevant severe weather reports.

Get Comprehensive Weather Timelines via MCP Server

Use `get_timelines` to pull data for specific metrics, like temperature or precipitation intensity. This function is designed for deep time-series analysis within your BigQuery workflow. It provides structured output ready for modeling. Your agent can take these raw timelines and feed them directly into a Gemini model for advanced predictive reasoning.

Setup guide

Set up Tomorrow.io Plus MCP in Google ADK

Prerequisites

Python 3.10+ installed
google-adk package (pip install google-adk)
Active Vinkius subscription with a valid endpoint token

1

Install Google ADK

Run pip install google-adk to install the Agent Development Kit. MCP support is included via the McpToolset class.
2

Connect via SSE transport

Use McpToolset.from_server() with SseServerParams pointing to your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Create an LlmAgent

Pass the returned mcp_tools list directly to LlmAgent(tools=mcp_tools). The ADK maps each MCP tool to a native Gemini function call — no manual schema definitions required.
4

Run with any Gemini model

The agent works with any Gemini model (gemini-2.0-flash, gemini-2.5-pro, etc.). Copy the full example on the right to get started with Tomorrow.io Plus tools in your ADK agent.

agent.py

from google.adk.agents import LlmAgent
from google.adk.tools.mcp_tool.mcp_toolset import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import SseServerParams

# Connect to the MCP via SSE
mcp_tools, exit_stack = await McpToolset.from_server(
    connection_params=SseServerParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    )
)

# Create your agent with auto-discovered tools
agent = LlmAgent(
    name="Tomorrow.io Plus_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Tomorrow.io Plus tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Tomorrow.io Plus MCP in Google ADK

Your LlmAgent calls `list_alerts` to get an immediate list of active warnings. Since you're using BigQuery, this data can be mapped directly onto existing operational datasets for faster analysis.

Absolutely. The `get_recent_history_weather` tool retrieves the last 24 hours of data, which you can then use to train or validate models running on your cloud infrastructure.

The `list_locations` tool shows all pre-defined account locations. If they aren't listed, you can use the agent to query for data using coordinates via other tools.

You need to call `get_forecast_weather`. This tool provides hourly and daily forecasts. Your Google ADK agent then uses this structured forecast data for predictive modeling within the cloud environment.

This MCP Server touches weather data: current conditions, historical records, and forecasts. Your agent ensures that only authorized personnel can access these specific environmental reports through Google Cloud.

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