2D Guillotine PackerをChatGPTとClaudeに接続

• 01 / 03レイアウトの自動化について
• 02 / 03スプライトシート作成を自動化する
• 03 / 03空間適合性の自動化について

最速日

506ms

最遅日

858ms

14日間の傾向

安定+4%

2D Guillotine Packer 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_QE7g1HY0ehCZ2CR6LMkpqQ3mw9PuboVh52TfHu6g/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 — 2D Guillotine Packer capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "2d-guillotine-packer-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_QE7g1HY0ehCZ2CR6LMkpqQ3mw9PuboVh52TfHu6g/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？ 2D Guillotine Packer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

  UI/UXデザイナー

  画面上の要素（ボタンや画像など）を、指定されたコンテナ内に隙間なく配置し、視覚的な効率を最大化したい方。

• 02

  ゲーム開発者

  多数のキャラクターやアイテムの画像（スプライト）を、アセットシートとして効率的にパックし、メモリ使用量を最適化したい方。

• 03

  Web開発者

  レスポンシブなレイアウトにおいて、要素間の隙間を最小限に抑え、正確な座標計算を行いたい方。

• 01

  What kind of problems does this MCP solve?

  This MCP solves 2D bin-packing problems. Essentially, it figures out the most efficient way to fit a collection of rectangular shapes into a larger, fixed container.

• 02

  Does it handle rotated items?

  The MCP is designed for rectangular items. While it handles complex geometry, the input must be defined as rectangles for the algorithm to run.

• 03

  What is the difference between the capabilities?

  The pack_rectangles capability finds the coordinates. The calculate_packing_density capability tells you the efficiency percentage of that placement. The validate_item_compatibility capability is just a quick check to see if any item is too big to start with.

• 04

  Do I need to worry about the container size?

  Yes, the container's bounding dimensions are the fixed limits for the entire operation. The MCP uses these boundaries to calculate all placements and densities.

• 05

  Is this MCP suitable for UI design?

  Absolutely. It's ideal for UI layout because it can confirm if all your elements fit within a specific viewport or screen size.

• 06

  How does the packing algorithm work?

  It uses a Guillotine split strategy. The algorithm sorts items by height in descending order and places them into available free rectangles, splitting any remaining space into two new smaller rectangles after each placement.

• 07

  Can items be rotated to improve fit?

  Yes, if the canRotate property is set to true for an item, the algorithm will attempt to swap its width and height if the original orientation does not fit in a free rectangle.

• 08

  What happens if an item cannot fit?

  If any single item in the input list cannot find a suitable free rectangle, the pack_rectangles capability returns a failure status and identifies the specific item ID that caused the error.

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