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 OpenAI Agents SDK 2 tools — connect in under 2 minutes

Name: Google Air Quality
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 2 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Google Air Quality through the Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails — no manual schema definitions required.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token — get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="Google Air Quality Assistant",
            instructions=(
                "You help users interact with Google Air Quality. "
                "You have access to 2 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from Google Air Quality"
        )
        print(result.final_output)

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.

The OpenAI Agents SDK auto-discovers all 2 tools from Google Air Quality through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Google Air Quality, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP

Follow these steps to integrate the Google Air Quality MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 2 tools from Google Air Quality

Why Use OpenAI Agents SDK with the Google Air Quality MCP Server

OpenAI Agents SDK provides unique advantages when paired with Google Air Quality through the Model Context Protocol.

Native MCP integration via `MCPServerSse` — pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

Google Air Quality + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the Google Air Quality MCP Server delivers measurable value.

Automated workflows: build agents that query Google Air Quality, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents — one queries Google Air Quality, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through Google Air Quality tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query Google Air Quality to resolve tickets, look up records, and update statuses without human intervention

Google Air Quality MCP Tools for OpenAI Agents SDK (2)

These 2 tools become available when you connect Google Air Quality to OpenAI Agents SDK 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 OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK

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

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

Google Air Quality + OpenAI Agents SDK FAQ

Common questions about integrating Google Air Quality MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.