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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use A/B Test Significance Calculator with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Stop guessing. Know if your changes actually work.

Included with plan

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

Complete set · 4 capabilities

The complete A/B Test Significance Calculator capability set.

These are the exact actions your AI can choose when you ask it to work with A/B Test Significance Calculator.

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

Observed, not estimated

648ms average. Fast in production.

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

Daily averagePeak 886ms
Aug 20Today
Fastest day
504ms
Slowest day
886ms
14-day trend
Slowing+11%

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

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.

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