AI Feature NPS Impact EngineをAIに接続

最速日

690ms

最遅日

1161ms

14日間の傾向

遅延傾向+15%

AI NPS Impact Engine 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_jHkDc4P6O0vpL4pfOavrHt2AJqoEz61FC4hG6fkc/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 NPS Impact Engine capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "ai-feature-nps-impact-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_jHkDc4P6O0vpL4pfOavrHt2AJqoEz61FC4hG6fkc/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 NPS Impact Engine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機能の市場適合性（PMF）を検証し、NPSへの影響度を定量化してロードマップに組み込むことができます。

• 02

  データアナリスト

  AI利用データとNPSデータを統合し、セグメント別、機能別の影響度を詳細に分析し、レポートを作成できます。

• 03

  プロダクトオーナー

  ユーザーの不満点（Detractor）を特定し、離脱リスクが高いユーザー層に焦点を当てた改善策を迅速に策定できます。

• 01

  Does this MCP tell me why users are unhappy with AI?

  It helps you pinpoint the risk. The evaluate_detractor_risk capability predicts the likelihood of becoming a detractor based on specific AI-related grievances, giving you the key areas to investigate.

• 02

  Can I use this to compare AI impact across different user types?

  Yes. You can use aggregate_segment_impact to get a high-level summary of how AI affects different user demographics, letting you compare groups easily.

• 03

  What kind of data does it need to calculate NPS lift?

  The calculate_nps_lift capability requires comparison data, specifically the NPS score before the AI feature was used and the score after its implementation.

• 04

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

  It's an analytics engine, not a dashboard. It gives you actionable metrics, like a quantified Value Perception score, which you can use directly in your product roadmap.

• 05

  How does the engine calculate NPS lift?

  The calculate_nps_lift capability calculates the absolute difference between the NPS of users interacting with the AI feature and the baseline NPS of users who do not.

• 06

  Can I predict user churn using this capability?

  Yes, by using evaluate_detractor_risk, you can predict the likelihood of users becoming detractors based on their AI satisfaction and specific grievances.

• 07

  What is the purpose of quantifying feature value?

  The quantify_feature_value capability translates NPS and satisfaction data into a business-centric metric that categorizes the feature as Essential, Nice-to-have, or a Commodity.

• 

  Product-Market Fit Diagnostic Engine AIコネクタ

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  AI Power User Analytics Engine AIコネクタ

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• 

  AI Feature Retention Analyzer AIコネクタ

  Quantify the impact of AI features on user retention and ROI.

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• 

  Feature Adoption Analytics AIコネクタ

  Quantify feature success through adoption velocity, saturation estimates, and retention impact modeling.

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