A/B Test Significance Calculator Connector for AI agents.
4 live capabilities
Determine if your experiment results are statistically significant
Waiting for input…
Why people use A/B Test Significance Calculator
A/B Test Significance Calculator for Fast Statistical Validation
This Connector changes that by letting your agent do the math for you. You just tell it the numbers, and it spits out the p-value, the uplift, and a clear verdict. You get to stop worrying about the math and start focusing on the strategy.
What Vinkius changes
You get a clear go or no-go decision on your experiment results in seconds.
Use it from Claude, ChatGPT, Cursor or another AI client you already have.
One account · 6,100+ Connectors
- Real-world use case 01
Landing Page Optimization
A marketer wants to know if a new headline drove more signups than the old one without doing manual math.
- Real-world use case 02
Checkout Flow Testing
An e-commerce lead needs to see if a one-click checkout reduced cart abandonment significantly.
- Real-world use case 03
Feature Flag Rollout
A product manager wants to validate a new navigation menu before it hits 100% of users.
Complete set · 4capabilities
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.
01—04
4 capabilities in this set.
Part of 4 available through A/B Test Significance Calculator.
- 01 Capability
Calculate required sample size
Calculate the required sample size per group for a new A/B test
- 02 Capability
Calculate statistical power
Calculate the current power of an ongoing test
- 03 Capability
Analyze conversion rab difference
Analyze the difference in conversion rates between two groups
- 04 Capability
Check peeking risk
Check the risk of peeking at A/B test results
Set up in minutes
One URL. Then ask A/B Test Significance Calculator to work.
Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use A/B Test Significance Calculator from the conversation.
Choose your client
Live previewAdvanced clients IDE · CLI
Claude · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_fzQ1aS9NSSO5zJk9otHteGWMsIrsHlHpW7aJ8mX9/mcp - Step 01
Open Connectors
In Claude Web or Claude Desktop, open Settings and choose Connectors.
- Step 02
Add the URL
Choose Add custom connector, name it A/B Test Significance Calculator, and paste the URL above.
- Step 03
Turn it on in chat
Select +, open Connectors, and enable A/B Test Significance Calculator for the conversation.
ChatGPT · Web + desktop
Connector URL · ready to paste
Streamable HTTPhttps://edge.vinkius.com/vk_preview_fzQ1aS9NSSO5zJk9otHteGWMsIrsHlHpW7aJ8mX9/mcp - Step 01
Open MCP settings
On desktop, open Settings and MCP servers. On web, open your workspace app or connector settings.
- Step 02
Add the URL
Choose Add server with Streamable HTTP, or create a custom MCP app, then paste the A/B Test Significance Calculator URL.
- Step 03
Save and start
Save the connection and enable A/B Test Significance Calculator in your conversation. Desktop may ask you to restart once.
Cursor · IDE configuration
Advanced setup
{
"mcpServers": {
"ab-test-significance-calculator": {
"url": "https://edge.vinkius.com/vk_preview_fzQ1aS9NSSO5zJk9otHteGWMsIrsHlHpW7aJ8mX9/mcp"
}
}
}- Step 01
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
- Step 02
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
- Step 03
Save the file
Cursor will automatically detect the new Connector
- Step 04
Start using A/B Test Significance Calculator
Open Agent mode in chat and ask: "Using A/B Test Significance Calculator, help me...". 4 tools available
VS Code Copilot · IDE configuration
Advanced setup
{
"mcpServers": {
"ab-test-significance-calculator": {
"url": "https://edge.vinkius.com/vk_preview_fzQ1aS9NSSO5zJk9otHteGWMsIrsHlHpW7aJ8mX9/mcp"
}
}
}- Step 01
Create MCP config
Create a .vscode/mcp.json file in your project root
- Step 02
Add the server config
Paste the JSON configuration above
- Step 03
Enable Agent mode
Open GitHub Copilot Chat and switch to Agent mode using the dropdown
- Step 04
Start using A/B Test Significance Calculator
Ask Copilot: "Using A/B Test Significance Calculator, help me...". 4 tools available
Windsurf · IDE configuration
Advanced setup
{
"mcpServers": {
"ab-test-significance-calculator": {
"url": "https://edge.vinkius.com/vk_preview_fzQ1aS9NSSO5zJk9otHteGWMsIrsHlHpW7aJ8mX9/mcp"
}
}
}- Step 01
Open MCP Settings
Go to Settings → MCP Configuration or press Cmd+Shift+P and search "MCP"
- Step 02
Add the server
Paste the JSON configuration above into mcp_config.json
- Step 03
Save and reload
Windsurf will detect the new server automatically
- Step 04
Start using A/B Test Significance Calculator
Open Cascade and ask: "Using A/B Test Significance Calculator, help me...". 4 tools available
Cline · IDE configuration
Advanced setup
{
"mcpServers": {
"ab-test-significance-calculator": {
"url": "https://edge.vinkius.com/vk_preview_fzQ1aS9NSSO5zJk9otHteGWMsIrsHlHpW7aJ8mX9/mcp"
}
}
}- Step 01
Open Cline MCP Settings
Click the Connectors icon in the Cline sidebar panel
- Step 02
Add remote server
Click "Add Connector" and paste the configuration above
- Step 03
Enable the server
Toggle the server switch to ON
- Step 04
Start using A/B Test Significance Calculator
Ask Cline: "Using A/B Test Significance Calculator, help me...". 4 tools available
Claude Code · Terminal command
Advanced setup
claude mcp add ab-test-significance-calculator --transport http "https://edge.vinkius.com/vk_preview_fzQ1aS9NSSO5zJk9otHteGWMsIrsHlHpW7aJ8mX9/mcp"- Step 01
Install Claude Code
Run npm install -g @anthropic-ai/claude-code if not already installed
- Step 02
Add the Connector
Run the command above in your terminal
- Step 03
Verify the connection
Run claude mcp to list connected servers, or type /mcp inside a session
- Step 04
Start using A/B Test Significance Calculator
Ask Claude: "Using A/B Test Significance Calculator, show me...". 4 tools are ready
Where the request belongs
Work A/B Test Significance Calculator can move forward.
This is for the growth lead who needs to justify a roadmap change to stakeholders or the data analyst who's tired of manual Excel formulas for every single test.
Growth Marketer
Validates if a new email subject line actually drove more clicks or if the change was negligible.
Product Manager
Decides if a new UI element is ready for a full release based on statistically significant user behavior.
Data Analyst
Checks the statistical integrity of an experiment to ensure the team isn't reacting to a false positive.
CRO Specialist
Determines the exact percentage lift of a new checkout button to report to the engineering team.
Build the capability set
Add more capabilities.
Each Connector adds new actions and data without changing how you work.
Browse Connectors
AB Test Sample Size Calculator
Calculate required sample size, test duration, and peeking risk for A/B experiments.
Bayesian A/B Testing Calculator
Quantify conversion probability, expected loss, and uplift using Bayesian inference.
Test Duration Calculator
Calculate required A/B test duration, sample sizes, and experiment risk levels.
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.
Multivariate Test Analyzer
Perform 2k factorial analysis to identify optimal element combinations and interaction effects in multivariate experiments.
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.
Bring your own AI
Change the model, client or framework. Keep A/B Test Significance Calculator connected.
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Claude -
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Vercel AI SDK
Before you connect
Questions about A/B Test Significance Calculator.
The practical details behind the request, access and result.
How does the A/B Test Significance Calculator help my team?
It handles the math for your experiments. Instead of manually calculating p-values and confidence intervals, your agent gives you the results instantly so you can make faster decisions on which features to ship.
Can I use this for any kind of A/B test?
Yes, it works for any test where you have visitor and conversion numbers. Whether you're testing headlines, buttons, or pricing, the Connector will calculate the significance and uplift for you.
What is a p-value and does this capability explain it?
A p-value tells you the probability that your results happened by chance. This Connector calculates the p-value for your specific data and then gives you a clear business recommendation on whether the result is reliable.
Will this help me avoid false positives in my experiments?
Definitely. By checking 90%, 95%, and 99% confidence levels, you can see exactly how much certainty you have before making a move, which helps prevent you from shipping changes that don't actually work.
Does it tell me if I should stop my test?
Yes, it provides a specific verdict. It looks at your significance and power metrics to give you a clear recommendation on whether to end the experiment or keep gathering more data.
Can I use the A/B Test Significance Calculator with Claude or Cursor?
Yes, it's designed to work with any MCP-compatible client like Claude, Cursor, or Windsurf. You just connect it to your agent and start asking questions about your test data.
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.
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.
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.
One connection away
Give your agent a direct line to A/B Test Significance Calculator.
Connect A/B Test Significance Calculator once. Keep it beside 6,100+ managed Connectors when the next task needs more.
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