Feature Scaler Engine MCP Connector for Claude

Neural Networks and K-Means clustering algorithms fail spectacularly if features aren't normalized. If an LLM attempts to subtract the mean and divide by the standard deviation across 5,000 rows, it will hallucinate 90% of the math.

This MCP brings deterministic Feature Scaling to your AI using simple-statistics. The AI specifies whether it wants Standard scaling (Mean=0, Variance=1) or MinMax scaling (Range 0-1), and the engine flawlessly transforms the target columns in milliseconds — returning the exact computed metrics for auditability.

The Superpowers

• Flawless Normalization: No LLM math hallucinations — exact scaling computed by your CPU.
• Multi-Column Support: Scale multiple features simultaneously in a single call.
• Automated Metric Extraction: Returns the exact Means, Std Devs, Mins, and Maxs used for scaling.
• Data Privacy: Your sensitive training data stays entirely on your machine.