How to Use the Wiagro MCP in OpenAI Agents SDK

Q: Can I use Wiagro with OpenAI Agents SDK for historical trends?

Absolutely. Tools like gettemperaturehistory pull time-series data (Celsius) over specific lookback periods. This is essential for figuring out if a hot spot was developing slowly.

Q: What kind of metadata does Wiagro provide to OpenAI Agents SDK?

You can use getsilobagdetails to get context before running any sensor check. This includes grain type and detailed information about the specific silobag you're looking at.

Q: Does Wiagro ensure data safety for OpenAI Agents SDK?

The system tracks sensor health using getsensorhealth. It provides IDs, battery levels, signal strength, and last communication time, so your agent knows if the underlying data source is reliable.

Get real-time grain data into your production agents with OpenAI Agents SDK.

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Connect Wiagro MCP to OpenAI Agents SDK

Create your Vinkius account to connect Wiagro 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.

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Setup Wiagro with OpenAI Agents SDK

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Track spoilage trends using CO2 history.

The `get_co2_history` tool pulls time-series CO2 data in ppm. This lets you track biological activity and detect spoiled grain early. You can feed this data into your OpenAI Agents SDK to build reliable, proactive quality assessment workflows.

Assess facility health with a single overview.

Use `get_facility_overview` when you need an overall picture of the entire storage site. It gives management a summary of all monitored silobags and units. Your OpenAI Agents SDK handles this high-level request, keeping your operational reports clean and immediate.

Monitor structural damage with rupture alerts.

`get_rupture_alerts` detects tears or holes in silobags. It returns the alert severity, location of the breach, and when it was detected. Your OpenAI Agents SDK can process these critical physical integrity alerts so you don't miss a single point of failure.

Setup guide

Set up Wiagro MCP in OpenAI Agents SDK

Prerequisites

Python 3.10+ installed
openai-agents package (pip install openai-agents)
Active Vinkius subscription with a valid endpoint token

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all Wiagro tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives Wiagro tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Wiagro tools and returns structured results. Copy the full example on the right to get started.

agent.py

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="Wiagro Agent",
            instructions="You have access to Wiagro tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Wiagro MCP in OpenAI Agents SDK

The MCP Server exposes multiple tools, letting your OpenAI Agents SDK access everything from temperature readings to facility overviews. It handles the data fetching and gives you clean, actionable results.

Absolutely. Tools like `get_temperature_history` pull time-series data (Celsius) over specific lookback periods. This is essential for figuring out if a hot spot was developing slowly.

You can use `get_silobag_details` to get context before running any sensor check. This includes grain type and detailed information about the specific silobag you're looking at.

The system tracks sensor health using `get_sensor_health`. It provides IDs, battery levels, signal strength, and last communication time, so your agent knows if the underlying data source is reliable.

It manages temperature, humidity, CO2 levels, and quality scores. These are all critical measurements that help determine grain safety and storage life.

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