Deterministic EdTech Quiz ScorerをAIに接続

• 01 / 03知識の欠落を分析する方法
• 02 / 03How to grade weighted quizzes
• 03 / 03試験の解答時間を算出する方法

最速日

709ms

最遅日

1144ms

14日間の傾向

安定+2%

Deterministic EdTech Quiz Scorer 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_H93VxPt23n4D3yjkszZDfL7mjHuwxVchcUVTD8BT/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 — Deterministic EdTech Quiz Scorer capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "deterministic-edtech-quiz-scorer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_H93VxPt23n4D3yjkszZDfL7mjHuwxVchcUVTD8BT/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？ Deterministic EdTech Quiz Scorer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

  EdTech 開発者

  複雑な採点ロジックや重み付け計算を、外部依存のない高速なエンジンで実装したいエンジニア。

• 02

  教育コンテンツ プロデューサー

  学習者の弱点をカテゴリ別に可視化し、パーソナライズされた学習体験を提供したい担当者。

• 03

  試験運営責任者

  標準化試験のような、厳密な配点管理と解答時間の分析が必要な評価プロセスを自動化したい管理者。

• 01

  What format should the quiz data be in?

  You must provide the answerKeyStr and userAnswersStr as stringified JSON arrays.

• 02

  Can I assign different points to different questions?

  Yes, the MCP supports a weighted scoring framework where you can set specific values for each question.

• 03

  How does it handle student weaknesses?

  It breaks down the results by category, allowing your agent to see exactly which subjects a student is struggling with.

• 04

  Does it track how long a student takes to finish?

  Yes, if you provide the totalTimeSeconds, it will calculate the average time spent per question.

• 05

  Which AI clients can use this MCP?

  You can use this with any MCP-compatible client, including Claude, Cursor, Windsurf, and VS Code.

• 06

  Why should I use an MCP instead of asking the AI to grade it?

  LLMs hallucinate math. If you give an LLM 50 questions, it will often miscount the correct answers, fail to apply fractional weights, or hallucinate the final percentage. This MCP uses deterministic V8 loops, guaranteeing 100% mathematical accuracy.

• 07

  How does the weighting system work?

  In your answerKey JSON array, you can add a weight parameter (e.g., weight: 2.5). The engine automatically tallies the maxPossibleScore and evaluates the user's earned points against it, rather than just doing a flat 1-point-per-question calculation.

• 08

  Does it track which questions the user got wrong?

  Yes. The output payload includes an array called incorrectQuestionIds, which isolates the exact IDs the user failed, allowing your AI to instantly provide targeted tutoring on those specific topics.

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