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Connect AI Feature Adoption Analytics to ChatGPT and Claude

Set it up once and it works in ChatGPT, Claude, Cursor, and any other client you love. It all runs safely in the background, so you can relax and focus on what really matters. Pinpoint exactly where your product growth is stalling.

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

Your AI does the work. We keep it safe and sound.

No other AI tool gives you this. Your workflow runs in the client you already love, your account stays protected, and you decide what the agent can and cannot do. It is the whole reason to make the switch.

Each Connector lives inside our infrastructure, the same place where your workflow runs. The three things below are already part of it, working quietly in the background so you never have to think about them. Nothing to add, nothing to set up, nothing to worry about.

A futuristic MCP client docking bay
V8 Isolate01

Each Connector runs inside its own sealed environment.

Each Connector runs inside its own sealed V8 runtime — no access to your files, your system, or other servers. A Connector never sees past its own request.

Kill Switch02

One switch stops every agent. Instantly.

One action deactivates every Connector, revokes every token, and ends every session at once. AI Governance keeps the record.

FinOps per User03

Spending limits that pause instead of surprise.

Every user keeps their own connections and credentials, isolated from everyone else. Anything that would cross your spending limit is held for your approval, not billed.

Three controls, built into the layer your AI connects through.

Curated set · 4 capabilities

We ship only the actions that matter.

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

    Get adoption summary

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

  3. 03

    Measure feature stickiness

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

  4. 04

    Calculate adoption velocity

    Determines how quickly users are moving through the adoption funnel

Real work

What teams actually run

01

Launching a New Feature

You just rolled out an AI writing capability. Use this MCP to determine if users are getting stuck during the setup process or if they are adopting it quickly enough.

02

Analyzing Quarterly Growth

Your team needs to prove ROI on AI investments. Use this to generate adoption metrics that go beyond simple sign-ups and show true stickiness.

03

Optimizing Onboarding Flows

If you see a drop-off point, this MCP helps you understand if the issue is discovery or if the feature itself is too complex to use.

04

Evaluating Feature Sunset

Before removing an old feature, use this to measure its current stickiness and determine if the user base still relies on it.

One connector, every AI

AI Feature Adoption Analytics works with the most popular AI clients.

These are the most popular clients, each with a step-by-step guide: one link, set up once, with governance and visibility built in. And because everything runs on the MCP standard, the same connection also works in any other compatible client — nothing to rebuild.

ClaudeClaudeChatGPTChatGPTGeminiGeminiPerplexityPerplexityGrokGrokMicrosoft CopilotMicrosoft CopilotCursorCursorVS CodeVS CodeWindsurfWindsurfJetBrainsJetBrainsClineClineLangChainLangChainVercel AI SDKVercel AI SDKLovableLovableZ.aiZ.aiRaycastRaycastQwen CodeQwen CodeKimi CodeKimi CodeLe ChatLe Chat

Building your own app? The connector is yours to use.

You don't need a client to put AI Feature Adoption Analytics to work: the same hosted connection plugs into your own applications and agent code, with the same governance on every request. Build with it, chat with it — one connection for both.

Observed, not estimated

812ms average. Fast in production.

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

Daily averagePeak 1022ms
Oct 3Today
Fastest day
648ms
Slowest day
1022ms
14-day trend
Stable+3%

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

Guided setup for Claude? Set up AI Feature Adoption Analytics in Claude and other AIs

See all the AI clients this connector works with ↑

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.

  • 05

    What metrics can I calculate?

    You can calculate adoption rates, adoption velocity (time to adoption), feature stickiness, and funnel efficiency.

  • 06

    How does complexity affect the results?

    Higher complexity increases the estimated time to adoption and can lower the stickiness score if not offset by user education.

  • 07

    Can I use this with Claude Desktop?

    Yes, this MCP server can be connected to Claude Desktop, Cursor, VS Code, Windsurf, and any other MCP-compatible client via Vinkius Edge.

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