AI Feature Error Metrics EngineをAIに接続

最速日

712ms

最遅日

1098ms

14日間の傾向

遅延傾向+11%

AI Feature Error Metrics 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_LsvWKro1aPjHLDI8WFIOQItScUwetDJC8byNtVSJ/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 Error Metrics capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "ai-feature-error-metrics-engine-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_LsvWKro1aPjHLDI8WFIOQItScUwetDJC8byNtVSJ/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 Error Metrics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

  ユーザーが直面する真のボトルネックを特定し、次の開発ロードマップを策定できます。

• 02

  DevOpsエンジニア

  AIシステムの安定性を定量的に測定し、運用上のリスクを最小限に抑えるためのメトリクスを提供します。

• 03

  SaaS開発者

  エラーを単なる数値として扱うのではなく、ビジネスインパクトのある指標として捉え直す手助けをします。

• 01

  Is this just a fancy error counter?

  No. It goes much deeper than raw counts. It calculates the user impact score, which tells you how much friction the error causes for the end user, not just how many times it happened.

• 02

  What kind of errors can it analyze?

  It handles common AI failures, such as Hallucinations or Model Timeouts, and helps you categorize them to understand their distribution across your user base.

• 03

  Do I need to be a data scientist to use this?

  No. The capabilities are designed to take raw metrics and translate them into simple, actionable statuses, like 'Critical' or 'Stable,' which product managers can use immediately.

• 04

  Does this MCP work with all AI clients?

  Yes. Since it's hosted on Vinkius, you connect once from any MCP-compatible client, including Claude, Cursor, and VS Code.

• 05

  How does this engine calculate user impact?

  The calculate_error_metrics capability calculates impact by weighing the error rate against user visibility and the system's ability to recover via automatic retries.

• 06

  Can I prioritize specific error types?

  Yes, use analyze_reliability_priorities to rank error types based on their frequency and assigned severity weights.

• 07

  What is the difference between error rate and effective error rate?

  The error rate is the total frequency of failures, while the effective error rate specifically tracks errors that were neither recovered by the system nor hidden from the user.

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