AI Feature Usage AnalyticsをAIに接続

最速日

729ms

最遅日

1019ms

14日間の傾向

安定0%

AI Feature Usage Analytics Connector

準備完了です。MCPクライアントを選択し、セットアップ手順に従ってください。

コネクタリンクhttps://edge.vinkius.com/vk_preview_NXLBxo4KbFu77cH9p5U7rwUVSPswlxRdaH1pfsRz/mcpコピー

Claude Desktop

以下の手順で数秒で接続できます。

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 Usage Analytics capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "ai-feature-usage-analytics-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_NXLBxo4KbFu77cH9p5U7rwUVSPswlxRdaH1pfsRz/mcp"
    }
  }
}

• Claude
• ChatGPT
• Cursor
• VS Code
• Windsurf
• Claude Code
• JetBrains
• Cline

各クライアントの手順ガイドはこちらです。 接続方法

Claude向けのガイド付きセットアップ？ AI Feature Usage AnalyticsをClaudeや他のAIに設定する

このConnectorが対応するすべてのAIクライアントを見る ↑

• 01

  プロダクトマネージャー

  AI機能の利用状況を把握し、次の開発ロードマップを決定する際に利用します。

• 02

  データアナリスト

  ユーザーセグメントごとの行動指標を比較し、統計的な傾向を導き出す分析に役立ちます。

• 03

  グロースマーケター

  エンゲージメントの推移を追跡し、ユーザーの定着率向上に向けた施策立案を行います。

• 01

  Does this MCP track all AI feature usage?

  The MCP provides deep insights into how users interact with AI capabilities. It is designed to calculate metrics like stickiness and usage distribution for the features you track.

• 02

  What is the difference between stickiness and engagement?

  Stickiness measures the ratio of daily to monthly active users for a segment. Engagement trajectory, however, tracks the overall direction and velocity of user interest over time.

• 03

  Can I compare different user groups?

  Yes. You can use the get_segment_comparison capability to compare AI engagement metrics across different user tiers, helping you spot performance gaps.

• 04

  Is this only for large companies?

  No. It helps any product team analyze their AI features. You can analyze usage intensity and engagement trends regardless of your company size.

• 05

  How is stickiness calculated?

  Stickiness is calculated using the get_stickiness_metrics capability, which divides daily active users by monthly active users.

• 06

  Can I compare different user tiers?

  Yes, use get_segment_comparison to compare average sessions and stickiness between segments like free, pro, or enterprise.

• 07

  What kind of usage distribution data is available?

  The get_usage_distribution capability categorizes users into low, medium, and high-frequency buckets based on their session counts.

• 

  AI Feature Discovery Analytics AIコネクタ

  Measure and optimize how users find and engage with your AI features.

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• 

  AI Power User Analytics Engine AIコネクタ

  Quantify AI power user density, value multipliers, and feature depth.

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• 

  AI Feature Adoption Analytics AIコネクタ

  Calculate AI feature adoption rates, velocity, stickiness, and funnel efficiency.

  表示
• 

  Product Usage & Engagement Engine AIコネクタ

  Analyze product stickiness, engagement scores, and user retention correlations.

  表示

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