How to Use the AirVisual MCP in Google ADK

Q: How do I load AirVisual tools into Google ADK?

You instantiate an MCP Toolset using StreamableHttpServerParameters with your Vinkius URL. Then you pass that toolset directly into the tools array of your LlmAgent.

Q: Can I restrict which AirVisual MCP tools my Google ADK agent sees?

You certainly can. The toolset accepts a toolnames filter so you can expose getstationdata while hiding the broader geographical listing tools.

Q: Will this work if my agent only has a user's IP address?

That is exactly what getnearestcitybyip is built to handle. The agent passes the IP, and the server returns the closest available weather and pollution data.

Feed live AirVisual AQI data directly into your Google ADK agents. Combine global pollution metrics with Gemini's long-context reasoning.

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Setup AirVisual with Google ADK

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Map global pollution with this MCP Server

Enterprise agents need real environmental data to cross-reference with internal BigQuery datasets. This integration gives your `LlmAgent` immediate access to `get_city_data` for live weather and AQI metrics through the MCP Server. Gemini models can hold massive amounts of context. Your agent can loop through `list_states` and `list_cities`, dumping thousands of local pollution readings into context before running a complex analysis.

Pinpoint stations using Google Cloud infrastructure

Broad city data only goes so far. When your Vertex AI application needs exact sensor readings, it triggers `get_station_data` to pull localized meteorological conditions. You restrict which operations the agent sees using the `tool_names` filter. If a specific agent only handles coordinate-based routing, you limit its MCP connection entirely to `get_nearest_city_by_coords`.

Resolve locations dynamically

Users rarely provide perfectly formatted geographical queries. Your Google ADK agent fixes this by hitting `list_countries` to validate the input before executing the final weather lookup. The setup works flawlessly over HTTP transports. If an incoming request only contains network data, the agent fires `get_nearest_city_by_ip` to figure out where the user actually is.

Setup guide

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

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Common questions about AirVisual MCP in Google ADK

You instantiate an MCP Toolset using `StreamableHttpServerParameters` with your Vinkius URL. Then you pass that toolset directly into the `tools` array of your `LlmAgent`.

You certainly can. The toolset accepts a `tool_names` filter so you can expose `get_station_data` while hiding the broader geographical listing tools.

That is exactly what `get_nearest_city_by_ip` is built to handle. The agent passes the IP, and the server returns the closest available weather and pollution data.

Gemini uses its massive context window to ingest the outputs of `list_countries` and `list_states`. It maps out the available regions before attempting to query a specific city.

Vinkius operates on a zero-trust, ephemeral architecture. The IP addresses and GPS coordinates your agent sends to resolve local AQI are processed instantly and wiped from memory.

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