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Connect A/B Test Significance Calculator to your AI

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. Know if your changes actually work.

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 · 4 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through A/B Test Significance Calculator.

  1. 01

    Calculate required sample size

    Calculate the required sample size per group for a new A/B test

  2. 02

    Analyze conversion rab difference

    Analyze the difference in conversion rates between two groups

  3. 03

    Calculate statistical power

    Calculate the current power of an ongoing test

  4. 04

    Check peeking risk

    Check the risk of peeking at A/B test results

Real work

What teams actually run

01

Testing a New Checkout Flow

You want to know if changing the checkout button color actually increases conversions. Use the MCP to analyze the difference between the old and new button groups.

02

Optimizing Signup Forms

You are launching a new signup flow. First, use the MCP to calculate how many users you need to see before you can declare a winner.

03

Analyzing Campaign Performance

A marketing campaign ran for two weeks. Use the MCP to check if the conversion rate increase is due to the campaign or just random variation.

04

Mid-Test Review

Your test is halfway through, and you're worried about stopping too early. Use the MCP to check the current statistical power and risk level.

Automate a task

Put A/B Test Significance Calculator 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

A/B Test Significance Calculator 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 A/B Test Significance Calculator 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

684ms average. Fast in production.

A/B Test Significance Calculator is checked daily against the live service.

Daily averagePeak 843ms
Oct 3Today
Fastest day
535ms
Slowest day
843ms
14-day trend
Stable-3%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 4 capabilities arrive 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 A/B Test Significance Calculator, so you can see the experience inside your AI.

It does not authenticate your account with A/B Test Significance Calculator. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

A/B Test Significance Calculator Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_fzQ1aS9NSSO5zJk9otHteGWMsIrsHlHpW7aJ8mX9/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 — A/B Test Significance Calculator capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ab-test-significance-calculator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_fzQ1aS9NSSO5zJk9otHteGWMsIrsHlHpW7aJ8mX9/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 A/B Test Significance Calculator in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work A/B Test Significance Calculator owners hand off.

Product Managers, Data Analysts, and CRO Specialists use this MCP to move beyond gut feelings. It provides the hard statistical proof needed to decide which product changes to ship. You hand off raw conversion data and test parameters to your AI client, and it returns a clear, actionable significance score.

  • 01

    Product Manager

    Determines if a feature change is worth the engineering effort by proving the impact.

  • 02

    Data Analyst

    Calculates the required sample size and monitors the statistical integrity of ongoing tests.

  • 03

    Marketing Director

    Validates campaign performance and determines if a new landing page layout is effective.

FAQ

Questions A/B Test Significance Calculator owners ask.

  • 01

    What is statistical significance?

    It's a measure that tells you if the difference you see in your test results is real, or if it just happened by chance. The MCP helps you determine if the difference is statistically significant based on your data.

  • 02

    Do I need to run this MCP for every test?

    If you are running A/B tests, yes. It's essential for planning the test size and for analyzing the results correctly. It prevents you from making bad decisions based on incomplete data.

  • 03

    What is 'peeking risk'?

    Peeking risk is the danger of checking your A/B test results too often before the test is complete. The MCP helps you check this risk to prevent false conclusions.

  • 04

    What data does this MCP need?

    The MCP requires specific metrics like conversion counts, total visitor numbers, and desired statistical parameters (like power and alpha) to run its calculations.

  • 05

    Can I use this for anything other than conversion rates?

    The MCP is designed for analyzing conversion differences between groups. It focuses on the statistical mechanics of comparing two distinct groups of data.

  • 06

    How can I check if my current A/B test results are significant?

    You can use the analyze_conversion_difference capability by providing the number of visitors and conversions for both your control and variant groups.

  • 07

    How do I know if I am checking my results too frequently?

    Use the check_peeking_risk capability to assess the risk level associated with multiple data inspections before reaching the target sample size.

  • 08

    Can I estimate how many users are needed for a new experiment?

    Yes, use the calculate_required_sample_size capability by specifying your baseline conversion rate and desired minimum detectable effect.

Explore

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