How to Use the AQICN MCP in OpenAI Agents SDK
Feed real-time air quality data directly into your OpenAI Agents SDK production pipeline.
Works with every AI agent you already use
…and any MCP-compatible client
Connect AQICN MCP to OpenAI Agents SDK
Create your Vinkius account to connect AQICN to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.
Instant location-based air quality for OpenAI Agents SDK
Your agent pulls live pollution numbers using `get_ip_feed` to determine the environment of the user. It skips manual entry by detecting coordinates automatically. This MCP Server handles the connection so your production code stays clean. The agent gets exact pollutant readings without extra configuration.
Scale your monitoring with OpenAI Agents SDK
Use `search_stations` to find specific sensors when your agent needs a broader view of a region. It queries the database to map out active monitoring points. This prevents your agent from guessing station names. It gets the correct UID every time, keeping your data flow stable.
Detailed station reporting for OpenAI Agents SDK
Call `get_station_feed` to pull granular weather and AQI metrics from specific hardware. Your agent displays this data instantly in the dashboard. It handles the raw JSON output from the hardware. You get reliable numbers for your safety-critical agent systems.
Set up AQICN MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all AQICN tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives AQICN tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate AQICN tools and returns structured results. Copy the full example on the right to get started.
import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerSse
async def main():
async with MCPServerSse(
url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
) as server:
agent = Agent(
name="AQICN Agent",
instructions="You have access to AQICN tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by AQICN. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.
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Real-time monitoring
Live
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Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.
Built-in savings
60%
lower AI costs
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place for every integration
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Common questions about AQICN MCP in OpenAI Agents SDK
Use it with your favorite AI tools
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