What's the difference between European AQI and US AQI?

The **European AQI** ranges 0-100+ with thresholds set by the EEA. The **US AQI** ranges 0-500 with EPA thresholds. Both are provided simultaneously so your AI can serve users in any region with their local standard.

Open-Meteo Air Quality MCP Server for OpenAI Agents SDK 4 tools — connect in under 2 minutes

Name: Open-Meteo Air Quality
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 4 Tools SDK

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

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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="Open-Meteo Air Quality Assistant",
            instructions=(
                "You help users interact with Open-Meteo Air Quality. "
                "You have access to 4 tools."
            ),
            mcp_servers=[mcp_server],
        )

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

asyncio.run(main())

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About Open-Meteo Air Quality MCP Server

Give your AI the power to assess air safety with real-time pollutant data at 11km resolution.

The OpenAI Agents SDK auto-discovers all 4 tools from Open-Meteo Air Quality through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries Open-Meteo Air Quality, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.

What you can do

Pollutant Concentrations — PM2.5, PM10, O₃, NO₂, SO₂, CO, dust, and ammonia in μg/m³
AQI Indexes — Both European (0-100+) and US (0-500) Air Quality Indexes with per-pollutant breakdowns
Pollen Forecast — Birch, grass, alder, ragweed, olive, and mugwort pollen counts for allergy planning
UV Index — Clear-sky and actual UV index for sun exposure safety

The Open-Meteo Air Quality MCP Server exposes 4 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 Open-Meteo Air Quality to OpenAI Agents SDK via MCP

Follow these steps to integrate the Open-Meteo 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 4 tools from Open-Meteo Air Quality

Why Use OpenAI Agents SDK with the Open-Meteo Air Quality MCP Server

OpenAI Agents SDK provides unique advantages when paired with Open-Meteo 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

Open-Meteo Air Quality + OpenAI Agents SDK Use Cases

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

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

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

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

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

Open-Meteo Air Quality MCP Tools for OpenAI Agents SDK (4)

These 4 tools become available when you connect Open-Meteo Air Quality to OpenAI Agents SDK via MCP:

get_air_quality

5, PM10, ozone, nitrogen dioxide, sulphur dioxide, and carbon monoxide concentrations for any location. Get air quality pollutant concentrations

get_aqi_index

Get Air Quality Index (European and US standards)

get_pollen_forecast

Get pollen and allergen forecast

get_uv_index

Get UV index forecast

Example Prompts for Open-Meteo Air Quality in OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Open-Meteo Air Quality immediately.

"Is the air quality in Beijing safe for outdoor exercise today?"

"What's the pollen forecast for Berlin this week?"

"What's the UV index in Sydney right now?"

Troubleshooting Open-Meteo Air Quality MCP Server with OpenAI Agents SDK

Common issues when connecting Open-Meteo 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.

Open-Meteo Air Quality + OpenAI Agents SDK FAQ

Common questions about integrating Open-Meteo 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.