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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use AI Engagement Scoring with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Stop guessing about user retention and product health.

Included with plan

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.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 4 capabilities

The complete AI Engagement Scoring capability set.

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

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Engagement Scoring.

  1. 01

    Analyze engagement trend

    Tracks how a user's interest in your AI features changes over time, showing you if their usage is trending up or down.

  2. 02

    Calculate user engagement score

    Determines a single, current engagement score for a specific user, giving you an immediate health check on their account.

  3. 03

    Get feature adoption metrics

    Evaluates how successfully specific AI features are being discovered by users and how often they are actually adopted.

  4. 04

    Predict user churn risk

    Identifies which users are most likely to abandon your AI features, allowing you to intervene before they leave.

Observed, not estimated

846ms average. Fast in production.

AI Engagement Scoring is checked daily against the live service.

Daily averagePeak 969ms
Aug 28Today
Fastest day
784ms
Slowest day
969ms
14-day trend
Improving-11%

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 AI Engagement Scoring, so you can see the experience inside your AI.

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

AI Engagement Scoring Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_4wOGVgGo4t204rkw2C4D4i8XjePsZ299pNnX5ev6/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 — AI Engagement Scoring capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-engagement-scoring-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_4wOGVgGo4t204rkw2C4D4i8XjePsZ299pNnX5ev6/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 AI Engagement Scoring owners hand off.

Product Managers and Growth Marketers use this MCP to move beyond vanity metrics. They need to know if users are actually finding value in the AI features, not just clicking around. This capability helps you prioritize product improvements based on real retention risk.

  • 01

    Product Manager

    Determines which features need immediate attention by analyzing adoption metrics and identifying low-value user segments.

  • 02

    Growth Marketer

    Builds targeted retention campaigns by flagging users with high churn risk and declining engagement trends.

  • 03

    Data Analyst

    Generates deep insights into user behavior, comparing discovery rates against actual value realization.

FAQ

Questions AI Engagement Scoring owners ask.

  • 01

    Does this MCP track all user activity?

    No, it focuses specifically on AI feature engagement. It helps you measure how users interact with your AI capabilities, providing metrics on adoption and value realization.

  • 02

    Can I use this for multiple product lines?

    The MCP is designed to analyze AI feature engagement. You must ensure the data source feeding the MCP covers all the AI features you want to measure.

  • 03

    What is the difference between engagement and adoption?

    Adoption metrics show if users are finding and trying a feature. Engagement scores give a holistic view of how valuable and active the user is with the product overall.

  • 04

    Is this only for large companies?

    No. This MCP helps any product team that needs to understand user retention and feature stickiness, regardless of company size.

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