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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use AI Feature Discovery Analytics 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 accelerate user engagement.

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 Feature Discovery Analytics capability set.

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

Capability set01 / 01

01-04

4 capabilities in this set.

Part of 4 available through AI Feature Discovery Analytics.

  1. 01

    Calculate discovery metrics

    Provides the fundamental health score of an AI feature's launch

  2. 02

    Evaluate channel performance

    Determines which marketing or UI paths are most successful at driving engagement

  3. 03

    Analyze discovery velocity

    Measures the speed of adoption and identifies delays in feature awareness

  4. 04

    Generate acceleration strategy

    Provides actionable advice to improve discovery based on current performance gaps

Observed, not estimated

852ms average. Fast in production.

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

Daily averagePeak 1068ms
Aug 28Today
Fastest day
744ms
Slowest day
1068ms
14-day trend
Slowing+13%

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

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

AI Feature Discovery Analytics Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_M2ugyR0bdwPEifqVrgkiN2rOjMAmxmSaK4RbYzhA/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 Discovery Analytics capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "ai-feature-discovery-analytics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_M2ugyR0bdwPEifqVrgkiN2rOjMAmxmSaK4RbYzhA/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 Discovery Analytics owners hand off.

Product Managers, UX Designers, and Marketing Analysts use this MCP to move beyond gut feelings about feature adoption. Instead of relying on anecdotal feedback, you get concrete data showing exactly where users are getting lost or discouraged. It helps you prove ROI on your product improvements.

  • 01

    Product Manager

    You use this to calculate the core discovery metrics and determine if a new feature is meeting adoption targets.

  • 02

    UX Designer

    You use it to analyze which UI placements cause friction, allowing you to redesign the user flow for better visibility.

  • 03

    Marketing Analyst

    You use it to evaluate which marketing channels or onboarding paths are most successful at driving initial user engagement.

FAQ

Questions AI Feature Discovery Analytics owners ask.

  • 01

    Does this MCP work for any type of feature, or just AI features?

    This MCP is specialized for measuring AI features within a SaaS product. It focuses on the unique challenges of user discovery and adoption for advanced, AI-driven capabilities.

  • 02

    What kind of data does the MCP need to run?

    The MCP needs usage data, including metrics like user counts, feature interaction counts, and timestamps. The prompt examples show how to provide this raw data for calculation.

  • 03

    Can I use this to compare different product versions?

    Yes. You can input data from different time periods or product versions to compare performance, helping you see if a change improved the discovery rate.

  • 04

    Is this MCP just a report generator, or does it give advice?

    It does both. After calculating metrics, the MCP can use the generate_acceleration_strategy capability to provide concrete, actionable advice on how to improve adoption.

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