MCP For Claude Marketplace
Correlation Matrix Engine

Correlation Matrix Engine MCP Connector for Claude

A+

Generate exact Pearson and Spearman correlation matrices across all numeric columns local. Find the strongest relationships in your data without LLM math errors.

1 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

Finding the exact Pearson correlation between 10 numeric columns requires computing 45 unique pairwise coefficients with perfect floating-point precision. No LLM can do this reliably.

This MCP delegates the computation to simple-statistics running locally. The AI passes a dictionary of named columns, and the engine builds the complete NxN correlation matrix, automatically extracting the top 5 strongest correlations.

The Superpowers

  • Zero Hallucination: CPU-computed coefficients with perfect precision.
  • Full NxN Matrix: Generates the complete correlation table across all column pairs.
  • Top-5 Extraction: Automatically surfaces the strongest relationships.
  • Data Privacy: Your sensitive data stays entirely local.
statisticscorrelationpearsonspearmanscience

1 tools expose this connector's capabilities to your AI agent.

calculate_correlation_matrix

Calculate exact deterministic correlation matrices (Pearson) across multiple datasets offline

See how to talk to your AI agent using Correlation Matrix Engine.

Find the exact Pearson correlation between all columns in this housing dataset.

The strongest relationship is between SquareMeters and Price (r = 0.89). The top 5 correlations have been extracted for your review.

Which features are most correlated with customer churn?

The strongest correlations with churn are: MonthlyCharges (r = 0.72), ContractLength (r = -0.68), and SupportTickets (r = 0.54).

Generate a Spearman matrix for this clinical trial data.

Strong monotonic relationship between Dosage and Response (ρ = 0.81). Age and Response show weak correlation (ρ = 0.12).

Pearson measures linear relationships and assumes normally distributed data. Spearman is rank-based, making it robust against outliers and ideal for non-linear monotonic relationships.

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