Statistical Process Control & Anomaly Alerts

Enables zero-dependency statistical analysis of numerical and time-series streams, flagging outliers via standard Z-score, modified median absolute deviation (MAD), and Tukey IQR fences. Also supports trend forecasting with Holt linear smoothing, multivariate gradient-descent regression, Welch's t-test hypothesis testing, and Power Iteration PCA dimensionality reduction through a native MCP stdio interface.

Monitors ML models in production for data drift and performance degradation, providing automated alerts and retraining recommendations.

Enables incident detection and analysis by identifying anomalies in metric time series and surfacing root-cause candidates and recommended actions. Supports both mock (synthetic) and VictoriaMetrics backends with identical MCP tool contracts for seamless development-to-production switching.

Timeseries anomaly analysis for fleet telemetry, delivered as an MCP server.