Skip to content
Vinkius

jstat Connector for AI agents.

1 live capability

Perform statistically significant hypothesis testing on categorical survey data.

Live agent request jstat / Connector

Waiting for input…

AI Agent

Why people use jstat

Stop LLM Math Hallucinations with Chi-Square Test Engine Statistics

This Connector lets you skip the manual setup entirely. You just tell your agent the observed numbers, and it handles the entire statistical pipeline. You get the exact p-value and degrees of freedom immediately, making your analysis faster and more reliable.

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

What Vinkius changes

You get mathematically perfect results for categorical data 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

    Marketing Correlation

    A brand wants to know if gender significantly affects subscription types.

  2. Real-world use case 02

    Customer Feedback

    An ops lead checks if complaint types are independent of product categories to see if one product line is failing.

  3. Real-world use case 03

    Education Trends

    A researcher tests if education level affects voting preference using survey data provided to the agent.

Complete set · 1capability

The complete jstat capability set.

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

Capability set01 / 01

01

1 capability in this set.

Part of 1 available through jstat.

  1. 01 Capability

    Calculate chi square

    Perform exact, deterministic chi-square tests of independence on categorical contingency tables. This eliminates math errors and provides the exact p-values needed for statistical significance.

Set up in minutes

One URL. Then ask jstat to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use jstat 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_3a81o44g9lK8eLsDLspiymfXnhfQOUzKsOVzwpSJ/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 jstat, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable jstat for the conversation.

Where the request belongs

Work jstat can move forward.

Built around the request

This is for data scientists, market researchers, and business analysts who need to prove relationships between categorical variables without doing manual calculations in a spreadsheet.

01

Market Researcher

Validating if demographic factors significantly impact product preference for a new launch.

02

Data Scientist

Performing hypothesis testing on categorical features in a machine learning pipeline.

03

Business Analyst

Checking if customer churn is independent of the support tier they were assigned to.

04

Academic Researcher

Running frequentist statistics on survey data for a peer-reviewed publication.

Build the capability set

Add more capabilities.

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

Browse Connectors
T-Test Statistics Engine logo
01 1 capability

T-Test Statistics Engine

Run exact Student's, Welch's, and Paired t-tests local. Get CPU-guaranteed p-values instead of LLM-hallucinated guesses.

View Connector
ANOVA Calculator Engine logo
02 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
Normality Test Engine logo
03 1 capability

Normality Test Engine

Test whether your data is normally distributed using Skewness and Kurtosis analysis local. Essential pre-check before running parametric statistical tests.

View Connector
Correlation Matrix Engine logo
04 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
05 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
A/B Test Significance Calculator logo
06 4 capabilities

A/B Test Significance Calculator

Calculate statistical significance, required sample sizes, and power for A/B tests.

View Connector

Bring your own AI

Change the model, client or framework. Keep jstat connected.

  • Claude
  • ChatGPT
  • Gemini
  • Cursor
  • VS Code
  • Windsurf
  • ZCode
  • Cline
  • Zed
  • Continue
  • Kiro
  • Roo Code
  • Zencoder
  • Goose
  • Void
  • Augment Code
  • Amp
  • Qodo
  • Tabnine
  • Pieces
  • Sourcegraph Cody
  • JetBrains
  • Warp
  • Amazon Q
  • Antigravity
  • BoltAI
  • Raycast
  • Jan
  • LM Studio
  • AnythingLLM
  • Open WebUI
  • Msty
  • Cherry Studio
  • LibreChat
  • TypingMind
  • Chorus
  • 5ire
  • n8n
  • LangChain
  • LlamaIndex
  • CrewAI
  • Vercel AI SDK

Before you connect

Questions about jstat.

The practical details behind the request, access and result.

How do I use the Chi-Square Test Engine for my survey data?

You just need to provide your AI client with the raw counts from your survey. The Connector will take those numbers, build the necessary matrices, and give you the p-value and chi-square statistic automatically.

Can this Connector handle large contingency tables?

Yes, it supports tables of various sizes, including 2x2, 3x3, and much larger matrices, making it suitable for complex categorical analysis.

Will my data be sent to a cloud server?

No. This Connector runs locally on your CPU, which means your sensitive business data or survey responses stay on your machine.

Is the math accurate or does it use AI?

The math is deterministic and handled by a dedicated engine, not by the AI's probabilistic reasoning. This prevents the common hallucinations where AI gets math wrong.

What is a p-value in this context?

The p-value tells you the probability that the relationship you see in your data happened by chance. A low p-value (usually under 0.05) suggests a significant relationship.

Can I use this for any kind of data?

It is specifically designed for categorical data. If you are looking to compare groups or check for independence between categories, this is the right capability.

What is a contingency table?

It's a matrix showing the frequency distribution of two categorical variables (e.g., rows = Gender, columns = Subscription Tier). The AI will automatically convert your raw data into this format.

Does it handle expected frequencies below 5?

The engine computes the result regardless, but the AI is instructed to warn you when expected frequencies are low, as the chi² approximation becomes less reliable in those cases.

Can it test more than two variables at once?

This engine performs a single pairwise independence test per execution. For multi-variable analysis, the AI can chain multiple calls to test different variable pairs sequentially.

One connection away

Give your agent a direct line to jstat.

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

Explore every Connector No credit card required · Free tier available