Download PDFMarkdown Version
ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use AI Feature Adoption Analytics with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Pinpoint exactly where your product growth is stalling.

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 AI Feature Adoption Analytics capability set.

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

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Feature Adoption Analytics.

  1. 01

    Get funnel efficiency

    Identifies where users are dropping off in the journey from discovery to adoption

  2. 02

    Calculate adoption velocity

    Determines how quickly users are moving through the adoption funnel

  3. 03

    Get adoption summary

    Provides a high-level overview of how well an AI feature is being adopted relative to the user base

  4. 04

    Measure feature stickiness

    Evaluates the long-term engagement and retention qualities of the AI feature

Observed, not estimated

798ms average. Fast in production.

AI Feature Adoption Analytics is checked daily against the live service.

Daily averagePeak 977ms
Aug 28Today
Fastest day
747ms
Slowest day
977ms
14-day trend
Slowing+9%

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

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

AI Feature Adoption Analytics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_kPh7GMdUh0ccRtys8n3BudGUf8P6eIEnwbFjqkXW/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 Feature Adoption Analytics capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-feature-adoption-analytics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_kPh7GMdUh0ccRtys8n3BudGUf8P6eIEnwbFjqkXW/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 Feature Adoption Analytics owners hand off.

Product Managers and Growth Leads use this MCP to move beyond simple usage counts. It helps them quantify the actual success of AI features and pinpoint specific friction points in the user journey. If you're responsible for product-led growth, this is for you.

  • 01

    Product Manager

    Determines if new AI features are meeting adoption goals and where the product needs friction fixes.

  • 02

    Growth Lead

    Uses the data to prove ROI on AI investments and optimize the user onboarding funnel.

  • 03

    SaaS Founder

    Gets a clear, quantitative view of product health without relying on anecdotal feedback.

FAQ

Questions AI Feature Adoption Analytics owners ask.

  • 01

    What kind of data does this MCP analyze?

    This MCP analyzes how AI features integrate into SaaS products. It calculates critical metrics like adoption rates, time to adoption, and feature stickiness.

  • 02

    Is this better than standard analytics capabilities?

    Yes. Standard capabilities often only count usage. This MCP accounts for factors like feature complexity and user education levels, giving you a much deeper understanding of product health.

  • 03

    Can I find out why users quit?

    The get_funnel_efficiency capability identifies where users are dropping off in the journey from discovery to adoption. This helps you pinpoint the exact friction point in your product.

  • 04

    Do I need to manage the connection?

    No. Vinkius hosts and manages this MCP. You connect your client once and gain access to the entire catalog.

Explore

More in Product Management

Suggestions