AI Feature Nsm AnalyzerをChatGPTとClaudeに接続

最速日

686ms

最遅日

1019ms

14日間の傾向

遅延傾向+11%

NSM Analyzer 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_yFt3TdlAk1TjCAGDiKY3X5VrqTckG0etrUBdM4oM/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 — NSM Analyzer capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "ai-feature-nsm-analyzer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_yFt3TdlAk1TjCAGDiKY3X5VrqTckG0etrUBdM4oM/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？ NSM Analyzer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

  機能の優先順位付けやロードマップ策定において、データドリブンな根拠を求められる方。

• 02

  データアナリスト

  複数の指標間の相関関係を分析し、ビジネスインパクトを数値化したい方。

• 03

  プロダクトオーナー

  短期的なKPI達成だけでなく、長期的な北極星指標(NSM)の改善に焦点を当てたい方。

• 01

  Does this MCP analyze real-time data?

  The MCP processes data to calculate impact and signals. It provides the mathematical framework for measurement, helping you understand the relationship between feature usage and your North Star Metric.

• 02

  What is the difference between NSM contribution and predictive strength?

  NSM contribution calculates the percentage of the metric movement tied to a feature. Predictive strength assesses how reliable a metric is as a signal for future growth.

• 03

  Can I use this to decide what to build next?

  Yes. The MCP provides a final priority ranking that combines both mathematical impact and strategic alignment, helping you make data-backed decisions for your roadmap.

• 04

  Is this capability only for AI features?

  While it is designed for AI features, the underlying framework measures the relationship between any feature usage and your core product goals.

• 05

  How is the AI contribution calculated?

  The contribution is determined by the product of the feature usage volume and its correlation strength, normalized against the total NSM value using the get_nsm_contribution capability.

• 06

  Can I use this to prioritize my product roadmap?

  Yes. By using rank_feature_priority, you can combine NSM contribution, indicator strength, and strategic alignment to generate a prioritized list of AI features.

• 07

  What are leading indicators in this context?

  Leading indicators are predictive metrics that move before the NSM. You can use evaluate_leading_indicator to determine how reliably these signals predict future North Star Metric changes.

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