- ALERTS
- TIMELINE
- HISTORY
- HUMAN
Short answer
How can I find grain spoilage risks with my AI?
Your AI uses temperature data to find hotspots and calculate the remaining time before spoilage occurs. You get specific alerts and countdowns for every bin at risk.
Where every issue lands.
Risk management outcomes
The AI sorts sensor data into actionable categories for your grain management.
ALERTS
Hotspot detection
The AI identifies specific locations in your bins where temperatures are rising. You receive immediate notice of localized heating.
TIMELINE
Spoilage countdowns
Your agent calculates the window of time remaining before grain quality degrades. This helps you prioritize which bins to move first.
HISTORY
Trend analysis
The AI reviews past temperature fluctuations to spot patterns. You can see if a heating event is accelerating or stabilizing.
HUMAN
Physical inspection
The AI flags the exact coordinates for you to check manually. You decide when to aerate or move the grain based on the data.
The workflow
What your AI does when the data arrives.
The AI handles the heavy lifting of monitoring sensor logs so you don't have to watch charts all day.
Scan for heat
The AI checks all active sensors to find any temperature spikes that indicate localized heating.
get_hotspot_alertsAssess the danger
Once a hotspot is found, the AI determines the likelihood of spoilage based on current conditions.
get_spoilage_riskReview the trend
The agent pulls the recent temperature logs to see how fast the heat is building up.
get_temperature_historyPredict the window
The AI combines the risk level and the temperature trend to tell you how many days you have left.
get_spoilage_risk
Try it
Copy these to start.
Paste these directly into your chat to begin monitoring.
Starting points
These are starting points. Swap out the bin names or sensor IDs with your actual data.
Grain Watch Connector
You're all set. Choose your MCP client and follow the setup instructions.
https://edge.vinkius.com/vk_preview_XN5VkLPw6XMatHSLfQyLUCDpI7Rxx1bplw4Thydj/mcpClaude Desktop
Follow the steps below to connect in seconds.
- 1In Claude Desktop, open Settings → Connectors.
- 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
- 3Click Add and start a new chat — Grain Watch capabilities are ready to use.
{
"mcpServers": {
"grain-watch-mcp": {
"url": "https://edge.vinkius.com/vk_preview_XN5VkLPw6XMatHSLfQyLUCDpI7Rxx1bplw4Thydj/mcp"
}
}
}Are there any active hotspot alerts in Bin 4?
Check the spoilage risk for the corn in the North Silo.
Show me the temperature history for the grain in Bin 12 over the last 48 hours.
Based on the current heating in Bin 7, how many days do I have before the grain spoils?
Claude
ChatGPT
Cursor
VS Code
Windsurf
Claude Code
JetBrains
Cline
Start here
Connect Grain Watch once, then ask.
One click connects your sensor data to your AI. Your credentials stay encrypted and secure.
Connect Grain Watch to your AIFAQ
How this task behaves
- 01
Can the AI turn on my aeration fans?
No. The AI only reads data and provides predictions. You must manually trigger any physical equipment.
- 02
Does the AI delete any sensor data?
No. The AI only retrieves information from your existing logs. It cannot modify or delete your historical data.
- 03
How accurate are the spoilage predictions?
The AI calculates the window based on the temperature history and current risk levels provided by the sensors.
- 04
Can I use this with any AI client?
Yes, as long as you are using an MCP-compatible client like Claude, Cursor, or Windsurf.
- 05
Will the AI notify me if a bin is getting hot?
Yes, the AI can identify hotspots and alert you through your chat interface.
More questions about Grain Watch? The Connector page answers them. See everything the Grain Watch Connector can do
Connect Grain Watch to Claude, Cursor, ChatGPT & more
