What is Minimum Detectable Effect (MDE)?

The MDE is the smallest change in your conversion rate that you want your test to be able to detect. You set this value because you don't want to run a massive test just to find a tiny, meaningless improvement.

Why is peeking risk dangerous?

Peeking risk means checking your test results before the predetermined time. This can cause you to see a temporary fluctuation that looks like a winner, but is actually just random chance, leading to false positives.

Do I need to know my daily traffic?

Yes, knowing your daily traffic helps the MCP estimate the test duration. If you don't provide it, the test cannot accurately project how long the experiment must run.

Is this for all types of testing?

This MCP focuses specifically on A/B testing and conversion rate analysis. It provides statistical rigor for comparing two versions of a feature or page.

How do I know if my sample size is sufficient?

You can use the calculate_required_sample_size capability. By providing your baseline conversion rate, MDE, confidence level, and statistical power, it will return exactly how many users you need per variant.

What is the risk of 'peeking' at my results?

Peeking refers to checking results and stopping a test before its planned duration. This significantly increases your False Positive rate. Use assess_peeking_risk to see if your current progress is safe or if you are at high risk of making an incorrect decision.

How can I estimate when my test will finish?

Once you have the total required users from the sample size capability, use estimate_test_duration along with your average daily traffic to calculate the estimated number of days needed for the experiment.

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Connect AB Test Sample Size Calculator to ChatGPT and Claude

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. Run statistically sound experiments and prove your hypotheses.

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.

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.

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 · 3 capabilities

We ship only the actions that matter.

Capability set01 / 01

01-03

3 capabilities in this set.

Part of 3 available through AB Test Sample Size Calculator.

01
Estimate test duration
Estimate the duration of an A/B test
02
Calculate required sample size
Determine the required sample size for an A/B test
03
Assess peeking risk
Assess the risk of stopping an A/B test early

Real work

What teams actually run

Optimizing Checkout Funnels

You want to test a new payment button color. Use this MCP to calculate how many users you need to run the test for a statistically reliable result.

Improving Onboarding Flows

After changing the first-time user experience, use the duration estimator to know exactly how long you must keep the test running.

Comparing Pricing Models

When comparing two pricing tiers, use the sample size calculator to ensure your user base is large enough to detect a meaningful difference in sign-ups.

Validating Feature Adoption

You rolled out a new dashboard feature. Use this to confirm the test is running long enough to capture all user segments.

Automate a task

Put AB Test Sample Size 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

AB Test Sample Size 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.

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

You don't need a client to put AB Test Sample Size 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

708ms average. Fast in production.

AB Test Sample Size Calculator is checked daily against the live service.

Daily averagePeak 895ms

Oct 3Today

Fastest day: 547ms
Slowest day: 895ms
14-day trend: Improving-13%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 3 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 AB Test Sample Size Calculator, so you can see the experience inside your AI.

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

AB Test Sample Size Calculator Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_r2w7FicRhYLb2yLUrh65lss0cEO4Bcdo5mApGeZ1/mcp

Claude Desktop

Follow the steps below to connect in seconds.

1In Claude Desktop, open Settings → Connectors.
2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
3Click Add and start a new chat — AB Test Sample Size Calculator capabilities are ready to use.

Configuration · claude_desktop_config.jsonCopy

{
  "mcpServers": {
    "ab-test-sample-size-calculator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_r2w7FicRhYLb2yLUrh65lss0cEO4Bcdo5mApGeZ1/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 AB Test Sample Size Calculator in Claude and other AIs

See all the AI clients this connector works with ↑

Who it's for

Built for the work AB Test Sample Size Calculator owners hand off.

This MCP is built for people who run data-driven experiments. If your job involves optimizing user flows, improving conversion rates, or proving product hypotheses, you need this. It takes the guesswork out of statistical planning.

01
Product Manager
Use this to validate whether a new feature change is statistically significant before committing engineering resources.
02
Data Analyst
Run precise calculations to determine the required sample size and test duration for any given metric.
03
Marketing Scientist
Assess the risk of stopping a campaign early, ensuring your marketing spend is backed by reliable data.

FAQ

Questions AB Test Sample Size Calculator owners ask.

01
What is Minimum Detectable Effect (MDE)?
The MDE is the smallest change in your conversion rate that you want your test to be able to detect. You set this value because you don't want to run a massive test just to find a tiny, meaningless improvement.
02
Why is peeking risk dangerous?
Peeking risk means checking your test results before the predetermined time. This can cause you to see a temporary fluctuation that looks like a winner, but is actually just random chance, leading to false positives.
03
Do I need to know my daily traffic?
Yes, knowing your daily traffic helps the MCP estimate the test duration. If you don't provide it, the test cannot accurately project how long the experiment must run.
04
Is this for all types of testing?
This MCP focuses specifically on A/B testing and conversion rate analysis. It provides statistical rigor for comparing two versions of a feature or page.
05
How do I know if my sample size is sufficient?
You can use the calculate_required_sample_size capability. By providing your baseline conversion rate, MDE, confidence level, and statistical power, it will return exactly how many users you need per variant.
06
What is the risk of 'peeking' at my results?
Peeking refers to checking results and stopping a test before its planned duration. This significantly increases your False Positive rate. Use assess_peeking_risk to see if your current progress is safe or if you are at high risk of making an incorrect decision.
07
How can I estimate when my test will finish?
Once you have the total required users from the sample size capability, use estimate_test_duration along with your average daily traffic to calculate the estimated number of days needed for the experiment.

Explore

More in Analytics

Connect AB Test Sample Size Calculator to Claude, Cursor, ChatGPT & more

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

Each Connector runs inside its own sealed environment.

One switch stops every agent. Instantly.

Spending limits that pause instead of surprise.

We ship only the actions that matter.

01-03

Estimate test duration

Calculate required sample size

Assess peeking risk

What teams actually run

Optimizing Checkout Funnels

Improving Onboarding Flows

Comparing Pricing Models

Validating Feature Adoption

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

AB Test Sample Size Calculator Connector

Claude Desktop

Product Manager

Data Analyst

Marketing Scientist

What is Minimum Detectable Effect (MDE)?

Why is peeking risk dangerous?

Do I need to know my daily traffic?

Is this for all types of testing?

How do I know if my sample size is sufficient?

What is the risk of 'peeking' at my results?

How can I estimate when my test will finish?

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