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Connect Normality Test Engine to ChatGPT, Claude and Gemini

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Stop guessing if your data fits parametric models.

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 1 capability

We ship only the actions that matter.

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through Normality Test Engine.

  1. 01

    Test normality

    Runs a deterministic Jarque-Bera test on your numeric data. It provides a clear verdict on normality without the risk of LLM math errors.

Real work

What teams actually run

01

Regression Pre-checks

Verify that residuals are normally distributed before finalizing a linear regression model.

02

Sensor Data Validation

Check if incoming sensor readings follow a normal curve or require non-parametric methods.

03

Confidence Interval Accuracy

Confirm normality in a column like 'Revenue' to ensure calculated confidence intervals are valid.

04

ANOVA Assumptions

Ensure data meets the normality requirement before running an ANOVA test.

Automate a task

Put Normality Test Engine to work on one thing.

Step-by-step automations your AI runs through this Connector: the workflow, the prompts to start with, and the exact capabilities behind each move.

One connector, every AI

Normality Test Engine works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put Normality Test Engine to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

898ms average. Fast in production.

Normality Test Engine is checked daily against the live service.

Daily averagePeak 1053ms
Oct 3Today
Fastest day
665ms
Slowest day
1053ms
14-day trend
Improving-11%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 1 capability arrives ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of Normality Test Engine, so you can see the experience inside your AI.

It does not authenticate your account with Normality Test Engine. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Normality Test Engine Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_WUlfcwTW8ijdRBrYjBDTpDiFw1dcKsTz5HdufzbG/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Normality Test Engine capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "normality-test-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_WUlfcwTW8ijdRBrYjBDTpDiFw1dcKsTz5HdufzbG/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

Guided setup for Claude? Set up Normality Test Engine in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work Normality Test Engine owners hand off.

This MCP is built for professionals who need to validate data assumptions before performing advanced statistical modeling.

  • 01

    Data Scientists

    They hand off raw datasets to their agent to verify distribution assumptions for regression models.

  • 02

    Academic Researchers

    They use it to ensure their experimental data meets the requirements for parametric testing.

  • 03

    Quantitative Analysts

    They rely on it to check sensor or financial data for skewness before running analysis.

FAQ

Questions Normality Test Engine owners ask.

  • 01

    How does this MCP prevent AI math errors?

    It uses the simple-statistics library to perform exact calculations locally. This means the AI doesn't do the math itself, so it cannot hallucinate the coefficients.

  • 02

    What statistical tests does it support?

    The MCP specifically performs the Jarque-Bera test to determine if a dataset follows a normal distribution.

  • 03

    Is my data sent to a cloud for processing?

    No. The computations are performed locally, ensuring your research data stays on your machine.

  • 04

    Which AI clients can use this MCP?

    You can use this with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

  • 05

    What information is returned after a test?

    The capability returns a pass/fail verdict, the p-value, the test statistic, and descriptive stats like Mean, Std Dev, Skewness, and Kurtosis.

  • 06

    Is this the Shapiro-Wilk test?

    This engine implements the Jarque-Bera normality test, which uses Skewness and Kurtosis. It is highly effective for medium-to-large samples and avoids the Shapiro-Wilk implementation gaps in JavaScript.

  • 07

    How many data points do I need?

    The Jarque-Bera test works best with 30 or more samples. For very small samples (n < 20), consider using visual QQ-plot analysis as a complement.

  • 08

    What does a 'not normal' result mean for my analysis?

    If your data is not normally distributed, parametric tests like t-tests and ANOVA may be unreliable. Consider using non-parametric alternatives like Spearman correlation or Mann-Whitney U tests.

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