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How to Use the AQICN MCP in Google ADK

Get live air quality metrics into your Google ADK environment on GCP.

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Google ADK

Connect AQICN MCP to Google ADK

Create your Vinkius account to connect AQICN 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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Map regional air quality with Google ADK

Use `get_map_bounds` to pull all active sensors within your defined latitude and longitude. Your agent then processes this for BigQuery exports. This gives your enterprise agents a clear picture of pollution trends. You avoid manual data scraping entirely.

Trigger alerts via Google ADK

The agent monitors specific cities using `get_city_feed` to detect spikes in pollutants. It then routes those alerts through your cloud infrastructure. This keeps your monitoring logic centralized. The agent acts on the data the moment it hits the server.

Connect hardware stations to Google ADK

Target specific hardware by UID with `get_station_feed` to verify local conditions. Your agent reconciles this with your existing weather datasets. This ensures your long-context agents have precise data. It eliminates the need for external API wrappers.

Setup guide

Set up AQICN 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. 1

    Install Google ADK

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

  2. 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. 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. 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 AQICN 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="AQICN_agent",
    model="gemini-2.0-flash",
    instruction="You have access to AQICN tools via MCP.",
    tools=mcp_tools,
)

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AQICN. 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.

Why Choose Vinkius

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Real-time monitoring

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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

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Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about AQICN MCP in Google ADK

You import the McpToolset and point it at the Vinkius HTTP endpoint. The agent then registers the tools as native functions.
Yes. The server supports standard HTTP transports. It fits directly into your existing agent pipeline on Google Cloud.
Your sensor requests are processed in an ephemeral sandbox. No station logs persist on the server once your agent receives the feed.
Use the tool_names filter during setup. This restricts the agent to only the specific functions you want it to execute.
Yes. The server handles large requests efficiently, allowing your Gemini models to process station data alongside your million-token context windows.

Start using the AQICN MCP today

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We've already built the connector for AQICN. Just plug in your AI agents and start using Vinkius.

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