CheckmarxをChatGPT、Claude、Geminiに接続

• 01 / 02IaCの監査方法
• 02 / 02脆弱性を修正する

最速日

827ms

最遅日

1148ms

14日間の傾向

改善傾向-20%

Checkmarx 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_thwJCCvAxQj2dRXly3vkJnbbHvTu7jJNcAvioyvo/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 — Checkmarx capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "checkmarx-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_thwJCCvAxQj2dRXly3vkJnbbHvTu7jJNcAvioyvo/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？ Checkmarx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

  セキュリティエンジニア (AppSec)

  メインのワークステーションやチケット管理ツールを離れることなく、脆弱性のトリアージをシームレスに実行できます。

• 02

  DevOps & プラットフォームチーム

  デプロイ前に、ステージングブランチにおけるKICSの構成ミスをエージェントを通じて直接調査できます。

• 03

  開発者

  ゼロデイ脆弱性の正確な修正箇所（BFL）を即座に特定し、LLMにロジックの書き換えを依頼できます。

• 01

  How do I connect this MCP to my Checkmarx environment?

  You need to provide a valid Checkmarx One JWT Token. Once you add this to the MCP settings in Vinkius, it is ready to use in your AI client.

• 02

  Which AI clients can I use with this MCP?

  This MCP works with any compatible client, including Claude, Cursor, Windsurf, and VS Code.

• 03

  Can I stop a scan if it is taking too long?

  Yes, you can use the cancel_scan capability to stop an active scan through your agent.

• 04

  Does this handle Infrastructure as Code security?

  Yes, the get_kics_results capability provides findings for Terraform, Dockerfiles, and Kubernetes YAML.

• 05

  What is Best Fix Location (BFL)?

  BFL is a feature that identifies the most effective spot in your code to apply a patch to resolve a specific vulnerability.

• 06

  How can the AI help me fix a vulnerability faster?

  Once an issue is identified via scan results, ask your agent to pull the 'Best Fix Location' (BFL) using the query ID. Checkmarx mathematically finds the common root code block, and your AI can instantly rewrite that exact block to sanitize the flaw. You save hours tracing code paths.

• 07

  Can the agent initiate a static code scan independently?

  Yes! Tell the agent to 'Run a scan on project ID X targeting the main branch'. It initiates the analysis array natively across Checkmarx One engines. You can poll for completion status later and retrieve the new dataset directly via chat.

• 08

  Does it segregate AppSec results from Cloud infrastructure flaws?

  It does. Application flaws are pulled cleanly via get_scan_results, whereas misconfigurations tied to Docker, Kubernetes, or Terraform limits use a dedicated get_kics_results pipeline. The agent intrinsically separates the context for your DevOps team.

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