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Vinkius

Deterministic Feature Flag Evaluator Connector for AI agents.

3 live capabilities

Ensure consistent feature rollouts and stable user experiences.

Live agent request Deterministic Feature Flag Evaluator / Connector

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AI Agent

Why people use Deterministic Feature Flag Evaluator

Stop feature flicker with Deterministic Feature Flag Evaluator

This Connector lets you run these checks directly within your AI client. You get instant, mathematically verified answers about who sees what, without ever leaving your workflow.

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

What Vinkius changes

You get a mathematically consistent way to test and verify rollouts through your AI agent.

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

One account · 6,100+ Connectors

  1. Real-world use case 01

    Catching uneven rollouts

    An engineer notices some users are getting different experiences and uses verify_distribution to find the error.

  2. Real-world use case 02

    Testing beta features

    A developer asks their agent to check if a specific test ID is correctly included in a new feature group.

  3. Real-world use case 03

    Debugging UI shifts

    A QA specialist uses evaluate_flag to confirm that a user's session won't flip-flop between old and new versions.

Complete set · 3capabilities

The complete Deterministic Feature Flag Evaluator capability set.

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

Capability set01 / 01

01—03

3 capabilities in this set.

Part of 3 available through Deterministic Feature Flag Evaluator.

  1. 01 Capability

    Evaluate flag

    Checks if a specific user meets the criteria for an enabled feature. It prevents unexpected UI changes during testing.

  2. 02 Capability

    Get flag config

    Pulls the current rules and settings for any flag key. This helps you understand exactly how a rollout is configured.

  3. 03 Capability

    Verify distribution

    Tests whether your percentage-based rollouts are distributed uniformly. It uses sampling to find deviations in your deployment.

Set up in minutes

One URL. Then ask Deterministic Feature Flag Evaluator to work.

Claude and ChatGPT only need the Connector URL. Copy it once, add it in settings, and use Deterministic Feature Flag Evaluator 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_mJg3N5dkuJ85CZUCtgsgYqCDidYVfave0kJ71YOn/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 Deterministic Feature Flag Evaluator, and paste the URL above.

  3. Step 03

    Turn it on in chat

    Select +, open Connectors, and enable Deterministic Feature Flag Evaluator for the conversation.

Where the request belongs

Work Deterministic Feature Flag Evaluator can move forward.

Built around the request

For engineers and DevOps professionals who need to ensure feature consistency during canary deployments or gradual rollouts.

01

DevOps Engineer

Verifying that a 5% rollout is actually hitting exactly 5% across the population.

02

Frontend Developer

Checking if a new UI component is correctly assigned to specific beta testers during development.

03

QA Engineer

Testing edge cases in feature logic without manually toggling flags in a dashboard.

Build the capability set

Add more capabilities.

Each Connector adds new actions and data without changing how you work.

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01 9 capabilities

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Manage LaunchDarkly feature flags, environments, assignments and deployments smoothly through conversational AI.

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02 4 capabilities

Feature Flag Rollout Calculator

Calculate deterministic user assignment, rollout projections, and statistical sample sizes for feature flags.

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03 8 capabilities

Flagsmith

Manage feature flags and remote config via Flagsmith. toggle features, manage identities, and update environment configurations directly from your AI agent.

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04 11 capabilities

Unleash (Feature Toggles)

Manage feature flags, strategies, and environments via Unleash. evaluate toggles, list projects, and monitor metrics directly from your AI agent.

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05 12 capabilities

Statsig

Manage feature flags, dynamic configs, and experiments. Evaluate gates and log events directly from your AI agent.

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Flipt logo
06 9 capabilities

Flipt

Manage feature flags and rollouts via Flipt. list namespaces, flags, segments, and rules directly from your AI agent.

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Bring your own AI

Change the model, client or framework. Keep Deterministic Feature Flag Evaluator connected.

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Before you connect

Questions about Deterministic Feature Flag Evaluator.

The practical details behind the request, access and result.

How does Deterministic Feature Flag Evaluator prevent UI flickering?

It uses CRC32 hashing to ensure that a user's assignment is tied to their ID. This means the result stays identical every time they load the page.

Can I use this Connector with Cursor or VS Code?

Yes, it works with any MCP-compatible client including Cursor, VS Code, and Claude Desktop.

How do I check if my 20% rollout is actually uniform?

You can simply ask your agent to run a distribution test using the verify_distribution capability on your specific flag.

Does this capability work for any user ID?

Yes, as long as you provide the user ID, the hashing logic will deterministically calculate their assignment status.

Can I see the specific rules for a flag?

You can use the configuration capability to pull all active rules and rollout percentages directly into your chat window.

How does the system ensure a user doesn't see a feature flicker?

The system uses CRC32 hashing of the flagKey and userId. Since these inputs are immutable for a specific user and flag, the resulting hash value remains constant, ensuring the feature state does not change between sessions.

Can I bypass the percentage rollout for specific users?

Yes. By providing an allowedIds list within the rulesJson parameter of the evaluate_flag capability, you can explicitly enable a feature for specific users regardless of the percentage rollout.

How do I verify if my rollout is actually distributed correctly?

You can use the verify_distribution capability. By specifying a target percentage and a sample size, the capability will simulate users and report if the observed distribution matches your expected rollout percentage.

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Give your agent a direct line to Deterministic Feature Flag Evaluator.

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