What is the Universal Air Quality Index (UAQI)?

The UAQI is Google's proprietary index that normalizes air quality measurements globally. It ranges from 0 to 100, where 100 is excellent and 0 is poor.

Can I check historical air quality for the past week?

Yes. The `get_air_quality_history` tool allows you to retrieve up to 720 hours (30 days) of historical data for any coordinate.

Are there specific advice for outdoor sports?

Yes. The health recommendations provide specific guidance for athletes and individuals performing intense physical activities outdoors based on the pollutant levels.

Google Air Quality MCP Server for AutoGen 2 tools — connect in under 2 minutes

Name: Google Air Quality
Availability: InStock
Author: Vinkius

microsoft.github.io/autogen/docs/tools/mcp-tools

Built by Vinkius GDPR 2 Tools Framework

Microsoft AutoGen enables multi-agent conversations where agents negotiate, delegate, and execute tasks collaboratively. Add Google Air Quality as an MCP tool provider through Vinkius and every agent in the group can access live data and take action.

Get MCP Server for AI Agents

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Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.tools.mcp import McpWorkbench

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with McpWorkbench(
        server_params={"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"},
        transport="streamable_http",
    ) as workbench:
        tools = await workbench.list_tools()
        agent = AssistantAgent(
            name="google_air_quality_agent",
            tools=tools,
            system_message=(
                "You help users with Google Air Quality. "
                "2 tools available."
            ),
        )
        print(f"Agent ready with {len(tools)} tools")

asyncio.run(main())

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About Google Air Quality MCP Server

Equip your AI agent with hyper-local environmental intelligence through the Google Air Quality MCP server. This integration provides real-time access to accurate air quality indexes, detailed pollutant concentrations, and actionable health recommendations for specific coordinates. Powered by Google's massive environmental data layer, your agent can retrieve the Universal Air Quality Index (UAQI), identify dominant pollutants (PM2.5, NO2, etc.), and access up to 30 days of historical data. Whether you are building health-tracking tools, planning outdoor events, or researching urban pollution, your agent acts as a dedicated environmental consultant through natural conversation.

AutoGen enables multi-agent conversations where agents negotiate, delegate, and collaboratively use Google Air Quality tools. Connect 2 tools through Vinkius and assign role-based access. a data analyst queries while a reviewer validates, with optional human-in-the-loop approval for sensitive operations.

What you can do

Real-time AQI Lookup — Get the current Universal Air Quality Index for any latitude/longitude.
Pollutant Breakdown — Identify dominant pollutants and their concentrations in specific areas.
Historical Auditing — Retrieve up to 720 hours of historical air quality data for trend analysis.
Health Advice — Access tailored recommendations for children, elderly, and sensitive groups.

The Google Air Quality MCP Server exposes 2 tools through the Vinkius. Connect it to AutoGen in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Google Air Quality to AutoGen via MCP

Follow these steps to integrate the Google Air Quality MCP Server with AutoGen.

Install AutoGen

Run pip install "autogen-ext[mcp]"

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Integrate into workflow

Use the agent in your AutoGen multi-agent orchestration

Explore tools

The workbench discovers 2 tools from Google Air Quality automatically

Why Use AutoGen with the Google Air Quality MCP Server

AutoGen provides unique advantages when paired with Google Air Quality through the Model Context Protocol.

Multi-agent conversations: multiple AutoGen agents discuss, delegate, and collaboratively use Google Air Quality tools to solve complex tasks

Role-based architecture lets you assign Google Air Quality tool access to specific agents. a data analyst queries while a reviewer validates

Human-in-the-loop support: agents can pause for human approval before executing sensitive Google Air Quality tool calls

Code execution sandbox: AutoGen agents can write and run code that processes Google Air Quality tool responses in an isolated environment

Google Air Quality + AutoGen Use Cases

Practical scenarios where AutoGen combined with the Google Air Quality MCP Server delivers measurable value.

Collaborative analysis: one agent queries Google Air Quality while another validates results and a third generates the final report

Automated review pipelines: a researcher agent fetches data from Google Air Quality, a critic agent evaluates quality, and a writer produces the output

Interactive planning: agents negotiate task allocation using Google Air Quality data to make informed decisions about resource distribution

Code generation with live data: an AutoGen coder agent writes scripts that process Google Air Quality responses in a sandboxed execution environment

Google Air Quality MCP Tools for AutoGen (2)

These 2 tools become available when you connect Google Air Quality to AutoGen via MCP:

get_air_quality_history

Get historical air quality data

get_current_air_quality

Get current air quality using Google Maps API

Example Prompts for Google Air Quality in AutoGen

Ready-to-use prompts you can give your AutoGen agent to start working with Google Air Quality immediately.

"What is the air quality in San Francisco right now?"

"Show me the air quality history for Tokyo for the last 24 hours."

"Are there any health warnings for Beijing today?"

Troubleshooting Google Air Quality MCP Server with AutoGen

Common issues when connecting Google Air Quality to AutoGen through the Vinkius, and how to resolve them.

McpWorkbench not found

Install: pip install "autogen-ext[mcp]"

Google Air Quality + AutoGen FAQ

Common questions about integrating Google Air Quality MCP Server with AutoGen.

How does AutoGen connect to MCP servers?

Create an MCP tool adapter and assign it to one or more agents in the group chat. AutoGen agents can then call Google Air Quality tools during their conversation turns.

Can different agents have different MCP tool access?

Yes. AutoGen's role-based architecture lets you assign specific MCP tools to specific agents, so a querying agent has different capabilities than a reviewing agent.