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Vinkius

ml-regression Connector for AI agents.

1 live capability

Get mathematically perfect regression coefficients and R-squared scores from raw data.

Live agent request ml-regression / Connector

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AI Agent

Why people use ml-regression

Curve Fitting Engine for Accurate Data Analysis

The Curve Fitting Engine lets you just paste your data into the chat. Your agent handles the rest, running the math locally to give you the exact coefficients and a fit score. You go from raw numbers to a perfect equation in seconds.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • Visual Studio Code
  • Windsurf

What Vinkius changes

You get mathematically perfect results without any AI hallucinations.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 5,900+ Connectors

  1. Real-world use case 01

    Sales Forecasting

    A retail manager wants to know the exact growth trend of a new product based on the last 6 months of sales data.

  2. Real-world use case 02

    Sensor Calibration

    An engineer needs to find the curve that maps raw voltage to temperature for a new hardware component.

  3. Real-world use case 03

    Scientific Research

    A biologist needs to fit a cubic polynomial to a growth curve from an experiment to find the rate of change.

Complete set · 1capability

The complete ml-regression capability set.

These are the exact actions your AI can choose when you ask it to work with ml-regression.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through ml-regression.

  1. 01 Capability

    Calculate regression

    Perform exact linear or polynomial curve fitting on your data points. It returns the full equation and a score to check the fit.

Set up in minutes

One URL. Then ask ml-regression to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use ml-regression from the conversation.

Choose your client

Live preview
Advanced clients IDE · CLI

Claude · Web + desktop

Official guide ↗

Connector URL · ready to paste

Streamable HTTP
https://edge.vinkius.com/vk_preview_GO1fBS3iBxNkA8lFrOVHJ7vN6YkFb6wEYYZNguMd/mcp
  1. Step 01

    Open Connectors

    In Claude Web or Claude Desktop, open Settings and choose Connectors.

  2. Step 02

    Add the URL

    Choose Add custom connector, name it ml-regression, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable ml-regression for the conversation.

Where the request belongs

Work ml-regression can move forward.

Built around the request

This is for data analysts, researchers, and engineers who need precise mathematical modeling and can't trust an AI to do the arithmetic correctly.

01

Data Analyst

You use this to double-check sales trends or growth rates without manually building complex formulas in a spreadsheet.

02

Research Scientist

You use this to fit curves to experimental data points to find exact rates of change for your papers.

03

Hardware Engineer

You use this to map raw sensor voltages to physical units using multi-degree polynomial curves.

Build the capability set

Add more capabilities.

Each Connector adds new actions and data without changing how you work.

Browse Connectors
Statistics Engine logo
01 5 capabilities

Statistics Engine

A zero-latency statistical engine to process datasets. Instantly compute the exact mean, median, mode, standard deviation, and percentiles completely local.

View Connector
Outlier Detection Engine logo
02 1 capability

Outlier Detection Engine

Identify statistical anomalies in massive datasets local using deterministic Z-Score and IQR methods. Stop LLMs from guessing which rows are outliers.

View Connector
RMSE & MAE Calculator logo
03 1 capability

RMSE & MAE Calculator

Compute exact Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) for regression models. Stop hallucinating model validation metrics.

View Connector
ANOVA Calculator Engine logo
04 1 capability

ANOVA Calculator Engine

Run exact One-Way ANOVA tests to compare means across multiple groups local. Get CPU-guaranteed F-scores and p-values, not LLM guesses.

View Connector
Correlation Matrix Engine logo
05 1 capability

Correlation Matrix Engine

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

View Connector
Data Analysis Prover logo
06 1 capability

Data Analysis Prover

A marketing team asked an AI to analyze campaign data. The AI reported 'significant correlation between email frequency and purchase rate (p<0.05).' The team tripled emails. Unsubscribes spiked 340%. Sample: N=47 self-selected respondents, no power analysis. Correlation: observational, no confounders. Distribution: right-skewed but mean used. p=0.043 but Cohen's d=0.12. trivial. Chart: truncated Y-axis making a 2% difference look enormous. This capability forces five axes: sample validity, causal inference, distribution awareness, significance with effect size, and visualization integrity.

View Connector

Bring your own AI

Change the model, client or framework. Keep ml-regression connected.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
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  • Windsurf
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  • Cline
  • Zed
  • Continue
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  • LibreChat
  • TypingMind
  • Chorus
  • 5ire
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  • LangChain
  • LlamaIndex
  • CrewAI
  • Vercel AI SDK

Before you connect

Questions about ml-regression.

The practical details behind the request, access and result.

Can the Curve Fitting Engine handle complex curves?

Yes, it supports multi-degree polynomial regression, which allows it to model complex, non-linear trends in your data.

Does the Curve Fitting Engine keep my data private?

Yes, all calculations are performed locally on your own machine, so your data never has to leave your environment.

How accurate are the results from Curve Fitting Engine?

The results are mathematically perfect. It uses a dedicated math engine to calculate coefficients rather than guessing.

Can I use Curve Fitting Engine for business sales data?

Absolutely. It's perfect for finding trends in sales, growth rates, or any other numerical dataset you have.

What is the difference between linear and polynomial regression in Curve Fitting Engine?

Linear regression fits a straight line, while polynomial regression fits a curve of various degrees to match complex data shapes.

Does Curve Fitting Engine work with any AI client?

Yes, it works with any MCP-compatible client, including Claude, Cursor, and Windsurf.

Does it calculate R-squared automatically?

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.

Can I specify the polynomial degree?

Yes! When choosing the 'polynomial' type, specify any degree (2 for quadratic, 3 for cubic, etc.) and the engine computes all coefficients with exact precision.

Do the X and Y arrays need to be sorted?

No. The internal ML engine matches X[i] to Y[i] regardless of the order. The regression computation is independent of how the data is sorted.

One connection away

Give your agent a direct line to ml-regression.

Connect ml-regression once. Keep it beside 5,900+ managed Connectors when the next task needs more.

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