Delivery Integrity ProverをAIに接続

• 01 / 03AIによるタスク完了の監査方法
• 02 / 03How to verify code
• 03 / 03コードの検証方法

最速日

714ms

最遅日

1382ms

14日間の傾向

遅延傾向+23%

Delivery Integrity Prover 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_47XZJ7Jwbw4wbyoAk0N57vFtYyOnkyNmEkgNiNe8/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 — Delivery Integrity Prover capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "delivery-integrity-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_47XZJ7Jwbw4wbyoAk0N57vFtYyOnkyNmEkgNiNe8/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？ Delivery Integrity Prover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

  AIエンジニア

  AIエージェントの出力が要件を満たしているか、厳格な検証プロセスを組み込みたい開発者。

• 02

  QAエンジニア

  AIによる自動生成コードのテスト結果や実行ログを、客観的な証拠として管理したい担当者。

• 03

  DevOpsエンジニア

  AIによるコード変更が、ビルドやテストのプロセスを正しく通過しているかを保証したい運用者。

• 01

  How does this MCP stop AI agents from lying?

  It requires empirical evidence, such as real terminal output and specific line numbers, rather than allowing the agent to provide descriptive summaries.

• 02

  Can I use this with Cursor or Windsurf?

  Yes, this MCP works with any MCP-compatible client including Claude, Cursor, and Windsurf.

• 03

  What happens if the agent fails the verification?

  The capability issues a rejection verdict highlighting exactly what is missing, such as unverified changes or unmapped requirements, forcing the agent to fix the issue.

• 04

  Does this replace my unit tests?

  No, it requires the agent to actually run your existing unit tests and provide the logs as proof of work.

• 05

  What are the 'pivots' mentioned in the capability?

  Pivots are the five criteria used to judge a task: requirement mapping, artifact modification, verification execution, gap identification, and overall integrity.

• 06

  Why are placeholder logs like 'tests passed' rejected?

  AI agents frequently assume that code works without executing it. Requiring actual command output logs forces them to run verification scripts, catching syntax errors and test failures early.

• 07

  What counts as a remaining gap?

  A remaining gap includes any manual check required by the user, edge cases that were explicitly left out of scope, or dependencies on other teams. Banning 'none' forces agents to acknowledge limitations.

• 08

  How does this prevent agents from lying about completion?

  It converts simple guidelines into strict capability-call checks. The agent must successfully match requirements to modified code lines and paste actual command outputs to get an approval verdict.

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