Rmse Mae CalculatorをChatGPTとClaudeに接続

• 01 / 03モデルの比較方法
• 02 / 03外れ値の検知方法
• 03 / 03回帰モデルの精度検証について

最速日

659ms

最遅日

1005ms

14日間の傾向

安定-2%

Native V8 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_7taOhFMQ4QeTOzapBajB7VxkIYnA7kpKNDVm5F0k/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 — Native V8 capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "rmse-mae-calculator-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_7taOhFMQ4QeTOzapBajB7VxkIYnA7kpKNDVm5F0k/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？ Native V8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

  Data Scientists

  They hand off prediction arrays to the agent to get instant, accurate validation metrics.

• 02

  Machine Learning Engineers

  They use the capability to compare different model architectures like Random Forest vs Neural Networks.

• 03

  Quantitative Analysts

  They rely on exact error calculations for financial or stock prediction models.

• 01

  How is this different from asking an AI to do math?

  AI models often approximate square roots and averages, leading to errors. This MCP executes the math in a native JavaScript environment to ensure the results are mathematically exact.

• 02

  Which AI clients can use this MCP?

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

• 03

  What specific metrics does it calculate?

  The capability calculates Mean Squared Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE).

• 04

  Do I need to host this myself?

  No, Vinkius hosts and manages the MCP for you. You just connect your client and start using the capabilities.

• 05

  Can I use this for comparing multiple models?

  Yes, you can provide prediction arrays from different models to your agent and have it use the capability to compare their error metrics.

• 06

  What is the difference between RMSE and MAE?

  RMSE heavily penalizes large errors (because the errors are squared before averaging), while MAE treats all errors equally linearly.

• 07

  Can it handle negative predictions?

  Yes, the exact mathematical formulas handle all floating-point numbers including negatives.

• 08

  Is this done local?

  Yes. All validation metrics are computed locally on the Vinkius Edge Runtime with zero external API calls, ensuring high privacy.

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