Curve Fitting Engine

Curve Fitting Engine MCP Connector for Claude

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Perform exact Linear and Polynomial regression on scatter plot data local. Get mathematically perfect coefficients, equations, and R-squared scores.

1 tools Official Updated Jun 28, 2026 Official Vinkius Partner

LLMs can explain the concept of a line of best fit, but when they try to calculate actual slopes, intercepts, and R² scores on real data, they hallucinate wildly.

This MCP delegates regression logic to ml-regression locally. Provide the AI with arrays of X and Y coordinates, and the engine computes the mathematically flawless linear or polynomial equation. You get precise coefficients and a guaranteed R-squared accuracy score — all without touching a cloud API.

The Superpowers

  • Zero Hallucination: Exact regression math performed locally by your CPU.
  • Polynomial Precision: Fit multi-degree curves (quadratic, cubic, or higher) effortlessly.
  • Automated R² Scoring: Generates the exact R-squared metric to validate model quality.
  • Data Privacy: Your experimental and business data stays entirely local.
regression-analysismathematical-modelingdata-processingstatistical-analysispolynomial-regressionlinear-regression

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

calculate_regression

Perform exact deterministic curve fitting (Linear, Polynomial) on scatter plot data

See how to talk to your AI agent using Curve Fitting Engine.

Fit a linear regression to this sales data and give me the exact slope and intercept.

The exact regression equation is y = 3.12x + 10.5, with an R-squared of 0.89, indicating a strong linear relationship.

Run a 3rd degree polynomial regression on these data points.

The polynomial equation is y = 0.5x³ − 1.2x² + 4x + 1. The fit score is R² = 0.98, indicating an excellent fit.

What is the exact intercept for this linear trend line?

The computed linear intercept is exactly −45.67. This means the baseline value before any X influence is −45.67 units.

Yes. Every regression model automatically returns the exact R-squared score. Values closer to 1.0 indicate a better fit, and the AI interprets this context for you.

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