How to Use the Xweather Renewable MCP in Google ADK

Q: How does Xweather Renewable work with the Google ADK?

You use McpToolset and pass it to your LlmAgent. Since this is built for enterprise cloud environments, the agent can act on structured data already residing in BigQuery.

Q: What type of planning support does Xweather Renewable provide with the Google ADK?

The server offers both getextendedforecast (for 15-day outlooks) and standard getweatherforecast. This gives your agent enough detail to plan both near-term operations and long-range maintenance.

Q: Can Xweather Renewable assist with site assessment using the Google ADK?

Yes. The agent can run checks like getwinddata for wind farm analysis, or pull data from getsolarirradiancedata to validate PV sites against existing infrastructure.

Q: What is the recommended flow when assessing Xweather Renewable with the Google ADK?

Start by calling searchlocations to get coordinates. Then, use those coordinates to run specialized tools like getcurrentconditions or getwinddata.

Connect Xweather Renewable to your BigQuery models using Google ADK.

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Connect Xweather Renewable MCP to Google ADK

Create your Vinkius account to connect Xweather Renewable 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 Xweather Renewable with Google ADK

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Perplexity

Access massive historical datasets.

The `get_historical_observations` tool retrieves weather data that's perfect for long-term trend analysis in BigQuery. You can validate your renewable energy models against years of recorded patterns. Similarly, `get_solar_irradiance_data` pulls historical solar readings. This lets the agent build robust time series data directly into your cloud environment.

Manage complex operational planning.

You'll need to check alerts before deployment. The `get_weather_alerts` tool sends critical advisories for asset protection during severe weather. This is a must-have for any enterprise agent. Furthermore, the `get_renewable_energy_farm_data` tool provides hourly forecasts and recent 5-minute production estimates, directly feeding into your energy trading pipelines.

Identify necessary physical locations.

Start by running `search_locations`. This returns place details—coordinates, elevation, and station metadata. It's the first step before asking for any specific weather data. The agent can also use `get_closest_weather_station` to get immediate details on a location once you have its coordinates from BigQuery.

Setup guide

Set up Xweather Renewable 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 Xweather Renewable 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="Xweather Renewable_agent",
    model="gemini-2.0-flash",
    instruction="You have access to Xweather Renewable tools via MCP.",
    tools=mcp_tools,
)

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Common questions about Xweather Renewable MCP in Google ADK

You use `McpToolset` and pass it to your LlmAgent. Since this is built for enterprise cloud environments, the agent can act on structured data already residing in BigQuery.

The server offers both `get_extended_forecast` (for 15-day outlooks) and standard `get_weather_forecast`. This gives your agent enough detail to plan both near-term operations and long-range maintenance.

Yes. The agent can run checks like `get_wind_data` for wind farm analysis, or pull data from `get_solar_irradiance_data` to validate PV sites against existing infrastructure.

Start by calling `search_locations` to get coordinates. Then, use those coordinates to run specialized tools like `get_current_conditions` or `get_wind_data`.

The server handles specific weather observations and energy generation forecasts. This includes operational production estimates, which you should manage carefully within your cloud governance.

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