Skip to content
Vinkius

Feature Flag Rollout Calculator Connector for AI agents.

4 live capabilities

Plan and manage deterministic feature flag rollouts with precise statistical projections.

Live agent request Feature Flag Rollout Calculator / Connector

Waiting for input…

AI Agent

Why people use Feature Flag Rollout Calculator

Feature Flag Rollout Calculator for Precise Deployment Math

With this Connector, you just ask your agent to do the work. It handles the hashing and the projections instantly. You get clear numbers on user impact and cohort overlap without ever opening a spreadsheet or running manual SQL queries.

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

What Vinkius changes

You get the math right every time without doing the heavy lifting yourself.

Use it from Claude, ChatGPT, Cursor or another AI client you already have.

One account · 6,100+ Connectors

  1. Real-world use case 01

    Verifying user inclusion in a rollout

    An engineer asks their agent if a specific ID is part of a new UI rollout.

  2. Real-world use case 02

    Predicting impact for a major launch

    A product manager wants to know how many users will see a new checkout flow.

  3. Real-world use case 03

    Detecting flag collisions

    A data scientist is worried about two flags colliding.

Complete set · 4capabilities

The complete Feature Flag Rollout Calculator capability set.

These are the exact actions your AI can choose when you ask it to work with Feature Flag Rollout Calculator.

Capability set01 / 01

01—04

4 capabilities in this set.

Part of 4 available through Feature Flag Rollout Calculator.

  1. 01 Capability

    Get user assignment

    Checks if a specific user falls within a rollout percentage using consistent hashing for stability.

  2. 02 Capability

    Project rollout impact

    Predicts the exact number of users affected at every stage of a planned deployment schedule.

  3. 03 Capability

    Analyze cohort overlap

    Estimates where two different feature flag populations intersect to prevent unintended behavior.

  4. 04 Capability

    Calculate statistical thresholds

    Determines the required user count in a treatment group to detect specific metric regressions.

Set up in minutes

One URL. Then ask Feature Flag Rollout Calculator to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Feature Flag Rollout Calculator 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_lSCWqvwFeIxZT5aRq7pxIFPfRB4jVj5nQX8h1rfL/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 Feature Flag Rollout Calculator, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Feature Flag Rollout Calculator for the conversation.

Where the request belongs

Work Feature Flag Rollout Calculator can move forward.

Built around the request

This is for the DevOps engineer who's tired of manual rollout math at 2am and the product manager who needs to know exactly how many users a new feature will hit before they hit 'go'.

01

DevOps Engineer

Validates that rollout percentages are hitting the right targets and checking for overlapping flags during deployment.

02

Product Manager

Plans the rollout schedule and ensures experiments have enough users to be statistically significant.

03

Software Engineer

Checks if a specific user ID is included in a feature group while debugging production issues.

Bring your own AI

Change the model, client or framework. Keep Feature Flag Rollout Calculator 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 Feature Flag Rollout Calculator.

The practical details behind the request, access and result.

How does the Feature Flag Rollout Calculator help with A/B testing?

It calculates the exact sample size you need to detect a regression. This ensures your results are statistically significant before you commit to a full launch.

Can I use the Feature Flag Rollout Calculator to check specific users?

Yes, you can ask your agent to verify if a specific user ID is included in a rollout. It uses consistent hashing to give you a definitive yes or no.

How do I know how many people will see a new feature?

You can ask the Connector to project the impact of different rollout stages. It will tell you the exact number of users affected at each percentage level.

Will the Feature Flag Rollout Calculator help prevent bugs from overlapping flags?

Yes, it estimates the intersection of multiple concurrent flags. This helps you identify if two features might be clashing for the same group of users.

Does the Feature Flag Rollout Calculator handle the actual toggling of flags?

No, this Connector handles the math and logic for rollouts. You still need your own system to store and toggle the flags themselves.

Why should I use this instead of a spreadsheet?

It's much faster and more accurate. It uses the same hashing logic your production system uses, so the numbers you see in your agent's chat are exactly what your users will experience.

How does the user assignment work?

The get_user_assignment capability uses consistent hashing of the User ID and Feature Key to ensure that a user's assignment remains deterministic at any given rollout percentage.

Can I use this for A/B testing?

Yes. You can use calculate_statistical_thresholds to determine the necessary sample size to detect a specific Minimum Detectable Effect (MDE) with your desired confidence level.

How do I estimate the impact of a multi-stage rollout?

Use project_rollout_impact by providing your total population size and a schedule of percentages to see both active and incremental user counts at each stage.

One connection away

Give your agent a direct line to Feature Flag Rollout Calculator.

Connect Feature Flag Rollout Calculator once. Keep it beside 6,100+ managed Connectors when the next task needs more.

Explore every Connector No credit card required · Free tier available