OpenAQ MCP Server for OpenAI Agents SDK 9 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect OpenAQ through the 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="OpenAQ Assistant",
instructions=(
"You help users interact with OpenAQ. "
"You have access to 9 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from OpenAQ"
)
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 OpenAQ MCP Server
Connect OpenAQ, the world's largest open air quality database, to any AI agent and monitor real-time pollution levels, track air quality trends, and access data from thousands of monitoring stations globally through natural language.
The OpenAI Agents SDK auto-discovers all 9 tools from OpenAQ through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns — chain multiple agents where one queries OpenAQ, another analyzes results, and a third generates reports, all orchestrated through the Vinkius.
What you can do
- Live Monitoring — Get the latest PM2.5, O3, NO2, SO2, and CO readings from any location worldwide
- Historical Analysis — Query time-series measurement data with date range filters for trend analysis
- Location Discovery — Browse monitoring stations by country, city, or geographic area
- Sensor Tracking — View active sensor devices and their measurement parameters
- Parameter Reference — Look up all measurable air quality parameters with units and classifications
- Global Coverage — Access data from 100+ countries with thousands of active monitoring locations
The OpenAQ MCP Server exposes 9 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 OpenAQ to OpenAI Agents SDK via MCP
Follow these steps to integrate the OpenAQ 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 9 tools from OpenAQ
Why Use OpenAI Agents SDK with the OpenAQ MCP Server
OpenAI Agents SDK provides unique advantages when paired with OpenAQ 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
OpenAQ + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the OpenAQ MCP Server delivers measurable value.
Automated workflows: build agents that query OpenAQ, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents — one queries OpenAQ, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through OpenAQ tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query OpenAQ to resolve tickets, look up records, and update statuses without human intervention
OpenAQ MCP Tools for OpenAI Agents SDK (9)
These 9 tools become available when you connect OpenAQ to OpenAI Agents SDK via MCP:
get_countries
Includes location counts and city counts per country. List countries with monitoring stations
get_latest_measurements
Useful for getting current air quality status without querying full history. Get latest measurements per location
get_location_by_id
Get details for a specific location
get_locations
Filter by country, city, parameter, or geographic bounding box. Returns location details including coordinates, sensor counts, and whether the station is an official monitor. List air quality monitoring locations
get_measurements
Filter by location, parameter, date range, and value range. Returns readings with timestamps. Get historical air quality measurements
get_parameter_by_id
Get details for a specific parameter
get_parameters
5, PM10, O3 (ozone), NO2, SO2, CO, etc. Includes units and whether each is a core parameter. List measurable air quality parameters
get_sensor_by_id
Get details for a specific sensor
get_sensors
Filter by location, parameter type, or active status. List air quality sensors
Example Prompts for OpenAQ in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with OpenAQ immediately.
"What's the current PM2.5 level in São Paulo, Brazil?"
"Which countries have the most air quality monitoring stations?"
"Show me ozone (O3) measurements from the last 24 hours in Paris."
Troubleshooting OpenAQ MCP Server with OpenAI Agents SDK
Common issues when connecting OpenAQ to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
OpenAQ + OpenAI Agents SDK FAQ
Common questions about integrating OpenAQ 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 OpenAQ 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 OpenAQ to OpenAI Agents SDK
Get your token, paste the configuration, and start using 9 tools in under 2 minutes. No API key management needed.