# Grain Watch MCP for AI Agents AI Agent Connect > Grain Watch lets you monitor your grain storage conditions in real-time using any AI agent. It tracks silo temperatures, humidity levels, and identifies hot spots to prevent spoilage before it happens. Instead of climbing silos or manually checking cables, you can ask your agent for a facility overview, get specific sensor data, or receive alerts on critical heating issues. It's built for anyone managing large-scale agricultural storage who needs to protect their inventory. ## Overview - **Category:** iot-hardware - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_XN5VkLPw6XMatHSLfQyLUCDpI7Rxx1bplw4Thydj/ai-agent-connect - **Tags:** silo-monitoring, temperature-sensors, humidity-tracking, predictive-maintenance, spoilage-risk ## Description Managing a grain storage facility is a constant battle against heat and moisture. You need to know what's happening inside every silo without physically being there at all times. This Connector connects your Grain Watch Silo Temperature Monitoring API to your preferred AI client, turning your agent into a dedicated storage analyst. Instead of digging through spreadsheets or logging into multiple dashboards, you can just talk to your agent to get the facts. You can ask about specific silo temperatures, check humidity trends to spot potential condensation, or get a full facility overview for a morning report. It handles the heavy lifting of monitoring sensor health and mapping out your layout, so you can focus on making decisions. Whether you're looking for a quick status check on a single unit or need to identify a developing hot spot that could ruin a whole crop, this connection makes that data accessible instantly. By bringing this into your workflow through Vinkius, you get a unified way to manage agricultural inventory safety without the manual headache of traditional monitoring. ## Tools ### get_alerts See all active alerts for temperature, humidity, and sensor issues across your facility. This helps you prioritize which silos need immediate attention. ### get_current_humidity Get current relative humidity readings from various sensor positions in a silo. Use this to detect moisture migration and condensation risks. ### get_current_temperature Fetch real-time temperature readings from the top, middle, bottom, and center zones of a silo. This helps you spot hot spots instantly. ### get_facility_overview Get a high-level summary of all monitored silos and their current temperature status. It's perfect for a quick morning status check. ### get_hotspot_alerts Retrieve specific alerts for localized heating that indicates a high risk of spoilage. This tool highlights the most critical issues first. ### get_humidity_history Pull historical humidity data to track moisture migration and condensation patterns over time. This helps you see how conditions have shifted. ### get_sensor_health Check the battery levels, communication status, and operational health of your sensor network. Use this to ensure your hardware is always online. ### get_sensor_map View the physical layout and installation depths of sensors within a specific silo. This helps you understand exactly where data is coming from. ### get_silo_details Get metadata for a specific silo, including grain type and sensor count. Use this to get context before analyzing storage conditions. ### get_silos List all grain silos monitored by the system including their names and locations. This is the best way to start an inventory check. ### get_spoilage_risk Get an AI-powered risk assessment including predicted days until spoilage if conditions persist. This helps you plan proactive interventions. ### get_temperature_history Access time-series temperature data to identify heating trends and hot spot development. Use this to see how a specific silo is warming up. ## Prompt Examples **Prompt:** ``` What's the status of my silos right now? ``` **Response:** ``` I've pulled the overview for your 12 monitored silos. Most are stable at 19.3C. However, Silo 7 (Corn) has a hot spot in the center-mid zone at 28.5C. All other units are within normal ranges. Would you like me to check the history for Silo 7? ``` **Prompt:** ``` Are there any alerts I should know about? ``` **Response:** ``` You have 1 critical alert: Silo 7 is showing a temperature spike of 7.2C above average. I also see 1 sensor in Silo 4 is currently offline for scheduled maintenance. Everything else looks good. Should I get more details on the Silo 7 alert? ``` **Prompt:** ``` Tell me about the risk in Silo 3. ``` **Response:** ``` Silo 3 (Wheat) currently has a **Low** spoilage risk. The temperature is stable at 18.5C with 82% humidity. If conditions persist, it's estimated to stay safe for at least 14 days. I recommend continuing routine monitoring. ``` ## Capabilities ### Track real-time silo temperatures Get current temperature readings from multiple sensor positions throughout the grain mass. ### Monitor humidity levels Track relative humidity to identify moisture migration and condensation risks. ### Identify developing hot spots Receive alerts for localized heating that indicates potential grain spoilage. ### Get spoilage risk assessments Receive AI-powered risk levels including predicted days until spoilage. ### Receive automated alerts Get notified about critical temperature, humidity, and sensor hardware issues. ### View historical trends Analyze past temperature and humidity patterns to detect long-term changes. ### Monitor sensor network health Check battery levels and communication status for all your storage sensors. ## Use Cases ### Identifying a heating silo An elevator operator sees a critical alert and asks the agent to use get_hotspot_alerts to find the exact zone. They then use get_temperature_history to see how fast it's rising. ### Assessing crop safety A farmer wants to know if their wheat is safe. They ask for a spoilage risk assessment on Silo 4, and the agent uses get_spoilage_risk to provide a risk level and specific actions. ### Generating a morning report A manager needs a summary for the team. They ask the agent to provide a facility overview using get_facility_overview and a list of all silos using get_silos. ### Troubleshooting moisture A consultant is investigating a wet spot. They use get_humidity_history to look for moisture migration patterns over the last 7 days in a specific unit. ## Benefits - Stop spoilage before it starts by using get_hotspot_alerts to catch localized heating early. - Save time on manual inspections by using get_facility_overview to see the status of every silo at once. - Protect grain quality by tracking moisture with get_current_humidity and get_humidity_history. - Maintain your hardware easily by checking battery and connection status with get_sensor_health. - Make faster decisions with get_spoilage_risk, which gives you predicted days until spoilage. - Understand your storage layout better by viewing sensor positions with get_sensor_map. ## How It Works The bottom line is you get instant, conversational access to your grain storage data without leaving your chat interface. 1. Subscribe to the Grain Watch MCP on Vinkius. 2. Enter your Grain Watch API key and base URL from your Grain Cloud dashboard. 3. Ask your AI agent to check silo temperatures, list active alerts, or provide a facility overview. ## Frequently Asked Questions **How does Grain Watch help with grain spoilage?** It gives you real-time data on heat and moisture, which are the biggest drivers of spoilage. By identifying hot spots early, you can take action before the grain is ruined. **Can I see the humidity levels in my silos?** Yes, you can ask your agent for the current humidity in any specific silo. It will report the relative humidity from multiple sensor positions to help you track moisture migration. **What happens if a sensor goes offline?** The Connector monitors sensor health for you. You can ask your agent which sensors are offline or check the battery levels of your wireless units to keep the system running. **Can I get a summary of my whole facility?** Yes, you can ask for a facility overview. Your agent will summarize the temperature status of all your monitored silos in one go, making it easy to see the big picture. **How do I know where my sensors are located?** You can ask the agent to show the sensor map for a specific silo. It will describe the layout, including top, middle, and bottom positions, as well as the installation depths. **Does this Connector show historical data?** Yes, you can ask for temperature or humidity history. Your agent can pull trends over specific timeframes to help you see how conditions have shifted. **Can it tell me if my grain is at risk?** Yes, it provides an AI-powered spoilage risk assessment. It looks at your current temperature, humidity, and grain type to give you a risk level and recommended actions. **Can my AI detect hot spots developing in my grain silos before spoilage occurs?** Yes! Use the `get_hotspot_alerts` tool to check for active hot spot detections across your silos. Hot spots are localized temperature increases that indicate early biological activity (mold, insects, or grain respiration) before visible spoilage. For trend analysis, use `get_temperature_history` to see how temperatures have been changing over the past days or weeks. Early hot spot detection gives you critical time to activate aeration and prevent grain loss. **How do I get the AI spoilage risk assessment for my silos?** Use the `get_spoilage_risk` tool with your silo ID. Grain Watch AI analyzes temperature trends, humidity patterns, and grain type to provide a risk level (low, moderate, high, critical), contributing factors, predicted days until spoilage if conditions persist, and recommended preventive actions. This combines multiple data sources into a single actionable assessment. For a facility-wide view, use `get_facility_overview` to see overall risk across all silos. **Can I check the health of my temperature sensors to ensure reliable monitoring?** Yes! Use the `get_sensor_health` tool with your silo ID to check the status of all temperature and humidity sensors. This shows which sensors are active, offline, or faulted, along with last communication times and battery levels for wireless sensors. You can also use `get_sensor_map` to see the physical layout of all sensors in a silo, helping you understand which zones each sensor monitors.