Verbinden Sie Deterministic EdTech Quiz Scorer mit Ihrer KI

• 01 / 03Wissenslücken analysieren
• 02 / 03Gewichtete Quizzes bewerten
• 03 / 03Prüfungsmetriken berechnen

Schnellster Tag

709ms

Langsamster Tag

1144ms

14-Tage-Trend

Stabil+2%

Deterministic EdTech Quiz Scorer Connector

Alles bereit. Wählen Sie Ihren MCP-Client und folgen Sie den Einrichtungsschritten.

Connector-Linkhttps://edge.vinkius.com/vk_preview_H93VxPt23n4D3yjkszZDfL7mjHuwxVchcUVTD8BT/mcpKopieren

Claude Desktop

Folgen Sie den Schritten unten, um sich in Sekunden zu verbinden.

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.

Konfiguration · claude_desktop_config.jsonKopieren

{
  "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

Schritt-für-Schritt-Anleitungen für jeden Client finden Sie im Guide. Verbinden

Geführte Einrichtung für Claude? Deterministic EdTech Quiz Scorer in Claude und anderen KI-Tools einrichten

Alle KI-Clients ansehen, mit denen dieser Connector funktioniert ↑

• 01

  EdTech Developers

  They hand off raw quiz JSON to the MCP to avoid writing custom grading logic.

• 02

  Instructional Designers

  They use the agent to quickly analyze student performance across different learning modules.

• 03

  AI Agent Builders

  They integrate this into evaluation workflows to provide deterministic grading results.

• 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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