# Centaur Analytics MCP for AI Agents AI Agent Connect > Centaur Analytics lets you manage and monitor grain storage from any AI client. You can pull real-time CO2, moisture, and temperature data from wireless sensors, get ML-powered spoilage risk scores, and generate full quality reports. It turns your AI into a grain quality analyst that tracks bin health, predicts spoilage days, and manages sensor battery levels across your entire facility. ## Overview - **Category:** iot-hardware - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_JAUlTOok6viAadhbZwv9ZjIVKtoBneQMgOzJf2Ty/ai-agent-connect - **Tags:** grain-monitoring, predictive-maintenance, sensor-data, storage-intelligence, spoilage-detection, agritech ## Description Centaur Analytics lets you manage and monitor grain storage from any AI client. Managing a grain facility usually means juggling dozens of tabs, manually checking sensor logs, and trying to spot the first signs of spoilage before it ruins a whole bin. It's a reactive game where one missed hot spot or a slight spike in CO2 can lead to massive losses. This Connector changes that by letting you talk to your data directly. Instead of digging through a dashboard to see if Bin 7 is holding up, you just ask your AI agent for a status update. It pulls the latest readings, checks them against historical trends, and tells you exactly what needs attention. You can monitor real-time CO2 levels to catch biological activity early, track moisture migration to prevent condensation issues, and get ML-powered risk assessments that predict exactly how many days you have left before your stock degrades. You can also get a full overview of your storage facility for executive reporting or generate detailed quality reports for insurance and marketing. It's a way to turn raw sensor data into actual decisions, like when to start aeration or how to price your current stock. By connecting this to your workflow via the Vinkius marketplace, you get a dedicated analyst that never sleeps. You stop guessing about grain quality and start making decisions based on what's actually happening inside the bins. ## Tools ### get_alerts This tool shows all active warnings for high CO2, rising temperatures, or sensor failures. Use it to see exactly what needs immediate attention. ### get_bin_details This tool pulls metadata for a specific bin, like grain type and current fill levels. It gives you the context you need before analyzing sensor data. ### get_bins This tool lists every grain storage bin monitored by the system with its current status. It helps you manage your inventory and find specific bins quickly. ### get_co2_history This tool shows historical CO2 levels to identify early signs of biological activity. It is useful for tracking spoilage trends over time. ### get_current_readings This tool fetches live CO2, moisture, and temperature data from all sensors in a bin. Use it to get an immediate look at current storage conditions. ### get_facility_overview This tool provides a high-level summary of your entire grain storage facility for executive reporting. It gives you a quick look at the overall health of your inventory. ### get_moisture_history This tool tracks moisture migration and condensation patterns over time. It helps you detect quality risks and assess drying effectiveness. ### get_quality_forecast This tool provides a simulation of what your grain quality will look like in the coming weeks. It helps you plan your marketing timing and storage duration. ### get_quality_report This tool generates a full condition assessment for a specific grain bin. It includes risk factors, test weight estimates, and actionable advice. ### get_sensor_health This tool shows battery levels and signal strength for your wireless sensor network. Use it to identify which sensors need maintenance or replacement. ### get_spoilage_predictions This tool gives you a risk level and an estimated count of days until spoilage begins. It helps you take proactive steps to preserve grain quality. ### get_temperature_history This tool reviews temperature trends to find hot spots or aeration issues. It is essential for identifying active spoilage or mold growth. ## Prompt Examples **Prompt:** ``` What's the risk level for the soybean bin in silo 4? ``` **Response:** ``` ### Spoilage Risk Assessment: Silo 4 (Soybeans) | Metric | Value | Status | | :--- | :--- | :--- | | **Risk Level** | **LOW** | ✅ Stable | | **Days to Spoilage** | **45+ Days** | ✅ Excellent | | **Confidence** | 87% | **Key Indicators:** * **CO2:** 780 ppm (stable trend) * **Moisture:** 12.8% (well below critical) * **Temperature:** Uniform at 10.5C **Recommendation:** Current storage conditions are optimal. No intervention required. Schedule next quality assessment in 14 days. ``` **Prompt:** ``` Give me a summary of our whole facility and any alerts. ``` **Response:** ``` ### Facility Overview * **Total Bins:** 18 * **Total Inventory:** 42,300 tonnes * **Avg. CO2:** 980 ppm * **Avg. Moisture:** 13.9% ⚠️ **Active Alerts:** 1. **Warning (Bin 7):** Moisture migration detected at top layer (15.2%). *Action: Targeted aeration recommended.* 2. **Info (Bin 12):** Sensor #8 battery at 15%. *Action: Schedule replacement within 2 weeks.* **Overall Status:** 16 of 18 bins in excellent condition. Facility quality score: 92/100. ``` **Prompt:** ``` Generate a quality report for bin 2. ``` **Response:** ``` ### Grain Quality Report: Bin 2 **Assessment Summary:** Bin 2 is currently holding in excellent condition. Moisture levels are stable, and temperature uniformity is high across all sensor depths. **Key Metrics:** * **Test Weight Estimate:** 62.4 lbs/bu * **Moisture Stability:** High * **Temperature Uniformity:** Excellent * **Mycotoxin Risk:** Low **Actionable Recommendations:** * Continue current aeration schedule. * No immediate intervention required. * Maintain current marketing price point for premium grade. ``` ## Capabilities ### Pull real-time sensor data Get live CO2, moisture, and temperature readings from multiple sensor positions throughout the grain mass. ### Get spoilage risk scores Receive ML-powered risk levels and a specific count of days until spoilage begins. ### Generate quality reports Create a full condition assessment including risk factors, test weight estimates, and actionable advice. ### Monitor active alerts Track threshold breaches for high CO2, rising temperatures, and sensor failures in real time. ### Track historical trends View time-series data for CO2 and moisture to identify migration patterns and biological activity. ### Manage bin inventory List and manage all grain storage bins, including fill levels, grain types, and monitoring status. ## Use Cases ### Spotting a hot spot A facility manager asks the agent to check for temperature spikes in the north wing and uses get_temperature_history to find a specific bin with rising heat. ### Marketing a crop A trader wants to know if the soybeans are still premium; they use get_quality_forecast to see if the quality will hold for another month. ### Routine maintenance An operator asks the agent to find all sensors with low batteries and uses get_sensor_health to create a replacement list. ### Rapid assessment A farmer needs a quick status on a new delivery and uses get_current_readings to see if the moisture levels are safe. ## Benefits - Stop guessing about spoilage with get_spoilage_predictions, which gives you a clear risk level and a countdown of days until quality drops. - Save time on reporting by using get_quality_report to automatically bundle sensor data and actionable recommendations into one document. - Catch issues early by using get_alerts to see immediate warnings about moisture migration or high CO2 levels before they become problems. - Optimize your marketing timing with get_quality_forecast to see how your grain quality will hold up over the next few weeks. - Maintain your hardware without manual checks by using get_sensor_health to see which wireless sensors need a battery swap. - Get a bird's-eye view of your entire operation with get_facility_overview to see average moisture and CO2 across every bin. ## How It Works The bottom line is you get a conversational interface for complex grain storage analytics. 1. Subscribe to the Connector and enter your Centaur API key and base URL from your dashboard. 2. Connect your preferred AI client to the Vinkius platform to link the data. 3. Ask your agent to check bin conditions, pull reports, or summarize your facility status. ## Frequently Asked Questions **Can Centaur Analytics help me predict when my grain will spoil?** Yes, it uses machine learning to provide a specific risk level and an estimated countdown of days until spoilage begins. This helps you move from reactive fixes to proactive management. **How does Centaur Analytics show me moisture migration?** It tracks moisture levels over time across different sensor positions. This allows you to see if moisture is moving into your grain or if condensation is forming. **Can I use Centaur Analytics to manage my sensor batteries?** Yes, it can identify exactly which sensors in your network are low on power or offline, allowing you to schedule maintenance without checking every bin manually. **Will Centaur Analytics help me with marketing my grain?** It provides quality forecasts that show how your grain quality is expected to hold up over the coming weeks, helping you time your sales for maximum profit. **Can I get a full report for my grain bins using Centaur Analytics?** Yes, it can generate a comprehensive condition assessment for any specific bin, including risk factors and actionable advice for your records. **How does Centaur Analytics handle CO2 tracking?** It monitors CO2 levels as a primary indicator of biological activity. By tracking these trends, it can alert you to potential spoilage long before it becomes visible. **Can my AI predict when grain spoilage will start in my storage bin?** Yes! Use the `get_spoilage_predictions` tool with your bin ID. Centaur AI analyzes CO2 trends, moisture patterns, and temperature data to predict spoilage risk (low, moderate, high, critical) and estimated days until spoilage onset. For deeper analysis, combine with `get_co2_history` to see the CO2 trend that drives the prediction. CO2 is the earliest spoilage indicator, often rising days before temperature changes become apparent. **How do I monitor CO2 levels to detect early signs of grain spoilage?** Use `get_current_readings` for real-time CO2 levels across all sensor positions in a bin, then use `get_co2_history` with a 30-day lookback to identify trends. CO2 levels above 1500 ppm indicate biological activity, and rising trends signal developing spoilage. Set up `get_alerts` to receive automatic warnings when CO2 exceeds safe thresholds. Early CO2 detection gives you 7-14 days more lead time than temperature-based monitoring alone. **Can I get an AI-generated quality report for a specific bin to share with buyers?** Yes! Use the `get_quality_report` tool with your bin ID to generate a comprehensive AI-powered quality report. This combines current sensor readings, historical trends, spoilage predictions, and quality forecasts into a single professional report including test weight estimates, moisture stability analysis, temperature uniformity, and mycotoxin risk evaluation. Perfect for buyer communications, insurance documentation, and quality certification.