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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use AI Onboarding Analyzer with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Pinpoint friction points and boost user adoption rates.

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 Onboarding Analyzer capability set.

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

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Onboarding Analyzer.

  1. 01

    Analyze funnel metrics tool

    Calculate core health indicators of the AI onboarding process

  2. 02

    Calculate optimization priority tool

    Recommend specific areas for product intervention based on complexity and friction

  3. 03

    Evaluate ttv efficiency tool

    Assess whether the time taken to reach value is acceptable given complexity

  4. 04

    Identify dropoff bottlenecks tool

    Pinpoint exactly where users are leaving the onboarding process

Observed, not estimated

817ms average. Fast in production.

AI Onboarding Analyzer is checked daily against the live service.

Daily averagePeak 1117ms
Aug 28Today
Fastest day
728ms
Slowest day
1117ms
14-day trend
Improving-16%

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 Onboarding Analyzer, so you can see the experience inside your AI.

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

AI Onboarding Analyzer Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_I6MNXh7ik3PUvZMfUqmmuSPnH8OdXAOBPkBfn087/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 Onboarding Analyzer capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-feature-onboarding-analyzer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_I6MNXh7ik3PUvZMfUqmmuSPnH8OdXAOBPkBfn087/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 Onboarding Analyzer owners hand off.

Product Managers, UX Designers, and SaaS Founders use this MCP to move beyond guesswork. It gives them quantitative data on why new AI features fail to stick. They hand off funnel data and user behavior metrics to the AI client to get immediate, actionable recommendations for improvement.

  • 01

    Product Manager

    Uses the MCP to calculate core health indicators and determine optimization priorities for the next sprint.

  • 02

    UX Designer

    Uses the MCP to identify drop-off bottlenecks and test hypotheses about user friction points.

  • 03

    SaaS Founder

    Uses the MCP to assess overall AI adoption efficiency and measure time-to-value risk.

FAQ

Questions AI Onboarding Analyzer owners ask.

  • 01

    Does this MCP work for all types of SaaS products?

    Yes. This MCP focuses on measuring the adoption efficiency of AI features. As long as your product has an onboarding flow and measurable user steps, this MCP can analyze it.

  • 02

    What kind of data do I need to provide?

    You need data points like the total number of users who started, the number who completed, and specific step names with associated user losses. The MCP handles the calculation from that input.

  • 03

    Is this just a dashboard, or does it give me recommendations?

    It's more than a dashboard. It provides actionable recommendations. For example, it can recommend simplifying feature entry if the complexity is high and the completion rate is low.

  • 04

    Can I use this to compare different feature versions?

    You can run the analysis multiple times with different data sets. This allows you to compare the funnel health score and drop-off rates between versions to see which one performs better.

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