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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use Retention Analytics with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Prove the value and ROI of your product features.

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

Waiting for input…

Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 4 capabilities

The complete Retention Analytics capability set.

These are the exact actions your AI can choose when you ask it to work with Retention Analytics.

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through Retention Analytics.

  1. 01

    Analyze usage correlation

    Measures the statistical link between AI feature usage frequency and user retention

  2. 02

    Calculate retention lift

    Calculates the percentage increase in retention attributed to the AI feature

  3. 03

    Estimate feature roi

    Estimates the ROI of an AI feature based on cost and prevented churn value

  4. 04

    Get segmented impact summary

    Provides a summary of AI feature impact across different user segments

Observed, not estimated

714ms average. Fast in production.

Retention Analytics is checked daily against the live service.

Daily averagePeak 840ms
Aug 28Today
Fastest day
714ms
Slowest day
840ms
14-day trend
Improving-15%

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 Retention Analytics, so you can see the experience inside your AI.

It does not authenticate your account with Retention Analytics. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

Retention Analytics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_MSHt7rUhQY5iWnADCndbfeH29Pk3aonUpoBsOFDO/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 — Retention Analytics capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-feature-retention-analyzer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_MSHt7rUhQY5iWnADCndbfeH29Pk3aonUpoBsOFDO/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 Retention Analytics owners hand off.

Product Managers and Data Analysts use this MCP to move beyond gut feelings. They need concrete data showing which AI features are worth the investment. This connector gives you the metrics to prove value to stakeholders and guide the product roadmap.

  • 01

    Product Manager

    Determines which AI features to build next by quantifying retention lift and ROI.

  • 02

    Data Analyst

    Checks the statistical link between usage frequency and long-term user stickiness.

  • 03

    Business Intelligence Lead

    Compares feature performance across different user segments to optimize resource allocation.

FAQ

Questions Retention Analytics owners ask.

  • 01

    Does this MCP only calculate retention lift?

    No. While calculating retention lift is a core function, you can also check the statistical correlation between usage and retention, estimate the feature's ROI, and summarize impact by user segment.

  • 02

    What kind of data does the MCP need to run?

    The MCP requires data points like usage group retention rates, non-usage group retention rates, feature costs, and projected churn values to run its calculations accurately.

  • 03

    Can I compare different user groups?

    Yes. The get_segmented_impact_summary capability allows you to compare how different user tiers or segments are affected by the AI features.

  • 04

    Is this for general analytics or specific AI features?

    It is specifically designed to measure the impact of AI-driven features. It helps you quantify the value of your AI investments, not general product usage.

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