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Vinkius

Native V8 Connector for AI agents.

1 live capability

Get mathematically precise regression metrics for your machine learning models.

Live agent request Native V8 / Connector

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AI Agent

Why people use Native V8

RMSE & MAE Calculator for Precise Machine Learning Validation

This Connector changes that by letting your agent handle the math directly. You just feed the arrays to your AI client, and it uses the calculation engine to give you the exact numbers. You get perfect MSE, RMSE, and MAE metrics without ever opening a spreadsheet.

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

What Vinkius changes

You get mathematically perfect validation metrics without the risk of 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

    Comparing Models

    A developer has a Random Forest and a Neural Network and needs to know which one has less variance error.

  2. Real-world use case 02

    Housing Price Prediction

    A data scientist wants to see how far off their linear model's house price predictions are from reality.

  3. Real-world use case 03

    Stock Value Analysis

    A financial analyst checks the MAE of a stock forecast to see the average dollar amount of error.

Complete set · 1capability

The complete Native V8 capability set.

These are the exact actions your AI can choose when you ask it to work with Native V8.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through Native V8.

  1. 01 Capability

    Calculate regression metrics

    Calculates exact RMSE, MAE, and MSE for regression model validation. This gives you precise error stats for your datasets and ensures your math is always correct.

Set up in minutes

One URL. Then ask Native V8 to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Native V8 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_7taOhFMQ4QeTOzapBajB7VxkIYnA7kpKNDVm5F0k/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 Native V8, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Native V8 for the conversation.

Where the request belongs

Work Native V8 can move forward.

Built around the request

Data scientists who can't risk hallucinated metrics in a research paper or a production deployment. It's for the ML engineer who needs to prove their model actually works.

01

Data Scientist

Validates regression models for housing price predictions on a Tuesday afternoon.

02

ML Engineer

Compares different neural network outputs to select the best production model.

03

Research Analyst

Checks the accuracy of stock price forecasts against historical data.

Build the capability set

Add more capabilities.

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

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02 1 capability

Confusion Matrix Engine

Deterministically calculate True Positives, FP, Precision, Recall, F1-Score, and Accuracy local. Stop LLM hallucinations when evaluating model metrics.

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03 1 capability

Curve Fitting Engine

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

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04 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.

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Arize AI

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K-Fold Split Engine

Generate rigorous, leak-proof cross-validation indices for train and test splits in machine learning pipelines.

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Bring your own AI

Change the model, client or framework. Keep Native V8 connected.

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Before you connect

Questions about Native V8.

The practical details behind the request, access and result.

What is the RMSE & MAE Calculator used for?

It is used for getting exact error scores for regression models, such as predicting house prices or stock values.

Can the RMSE & MAE Calculator handle large datasets?

Yes, it processes numeric arrays natively in JavaScript to give you precise metrics quickly without slowing down your workflow.

Will the RMSE & MAE Calculator help me find outliers?

Yes, by comparing the MAE and RMSE, you can see if your model is being skewed by extreme values in your data.

Is the RMSE & MAE Calculator accurate?

It provides mathematically pristine results because it uses a dedicated calculation engine rather than relying on the AI's internal logic.

Can I use the RMSE & MAE Calculator for stock predictions?

Definitely. It is a standard way to validate how well your agent is forecasting price movements against historical data.

How does the RMSE & MAE Calculator work with my AI?

You just give your agent the lists of numbers, and it uses the Connector to do the math for you instantly.

What is the difference between RMSE and MAE?

RMSE heavily penalizes large errors (because the errors are squared before averaging), while MAE treats all errors equally linearly.

Can it handle negative predictions?

Yes, the exact mathematical formulas handle all floating-point numbers including negatives.

Is this done local?

Yes. All validation metrics are computed locally on the Vinkius Edge Runtime with zero external API calls, ensuring high privacy.

One connection away

Give your agent a direct line to Native V8.

Connect Native V8 once. Keep it beside 5,900+ managed Connectors when the next task needs more.

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