IQAir MCP Server for OpenAI Agents SDK 6 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect IQAir through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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="IQAir Assistant",
instructions=(
"You help users interact with IQAir. "
"You have access to 6 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from IQAir"
)
print(result.final_output)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About IQAir MCP Server
Empower your AI agent to orchestrate your entire environmental research and air quality auditing workflow with IQAir, the world's most popular platform for air quality data. By connecting the AirVisual API to your agent, you transform complex pollution searches into a natural conversation. Your agent can instantly retrieve real-time air quality indices (AQI), audit weather conditions, and identify the most polluted areas without you ever touching a technical portal. Whether you are conducting climate research or monitoring local health constraints, your agent acts as a real-time environmental assistant, ensuring your data is always precise and localized.
The OpenAI Agents SDK auto-discovers all 6 tools from IQAir through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries IQAir, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- Pollution Auditing — Retrieve real-time Air Quality Index (AQI) data for the nearest city or specific global locations instantly.
- Weather Oversight — Audit current weather conditions, including temperature, humidity, and atmospheric pressure, to maintain a clear view of environmental scale.
- Geographic Discovery — List all supported countries, states, and cities in the IQAir catalog to understand the geographic reach of air quality monitoring.
- Local Intelligence — Query specific city data to understand local pollution markers and main pollutants (e.g., p2, p1).
- Operational Monitoring — Check API status to ensure your environmental research workflow is always operational.
The IQAir MCP Server exposes 6 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 IQAir to OpenAI Agents SDK via MCP
Follow these steps to integrate the IQAir 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 6 tools from IQAir
Why Use OpenAI Agents SDK with the IQAir MCP Server
OpenAI Agents SDK provides unique advantages when paired with IQAir 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
IQAir + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the IQAir MCP Server delivers measurable value.
Automated workflows: build agents that query IQAir, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries IQAir, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through IQAir tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query IQAir to resolve tickets, look up records, and update statuses without human intervention
IQAir MCP Tools for OpenAI Agents SDK (6)
These 6 tools become available when you connect IQAir to OpenAI Agents SDK via MCP:
check_api_status
Check if the IQAir API is operational
get_city_air_quality
Get real-time air quality and weather for a specific city
get_nearest_city_air_quality
Get real-time air quality and weather for the city nearest to the requester IP
list_supported_cities
List all cities supported for a specific state and country
list_supported_countries
List all countries supported by IQAir
list_supported_states
List all states supported for a specific country
Example Prompts for IQAir in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with IQAir immediately.
"What is the air quality in 'Los Angeles, California, USA' using IQAir?"
"Check air quality for my nearest city."
"List all cities supported in the state of 'Sao Paulo', Brazil."
Troubleshooting IQAir MCP Server with OpenAI Agents SDK
Common issues when connecting IQAir to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
IQAir + OpenAI Agents SDK FAQ
Common questions about integrating IQAir MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.Does the SDK support streaming responses?
Connect IQAir with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect IQAir to OpenAI Agents SDK
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.
