H2O.aiをChatGPT、Claude、Geminiに接続

• 01 / 03モデル指標を監査する方法
• 02 / 03クラスターの状況を確認する
• 03 / 03トレーニングジョブの監視方法

最速日

655ms

最遅日

986ms

14日間の傾向

遅延傾向+26%

H2O.ai 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_joJzJEG0t6WyiAGy91nhlV2uG13UXBw7Ejke9uIr/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 — H2O.ai capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "h2oai-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_joJzJEG0t6WyiAGy91nhlV2uG13UXBw7Ejke9uIr/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？ H2O.ai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

  データサイエンティスト

  クラスターのダッシュボードを個別に確認することなく、モデルのトレーニング状況やフレームデータを監視できます。

• 02

  MLエンジニア

  自然言語での対話を通じて、モデルアーキテクチャの監査やデプロイステータスの追跡を行えます。

• 03

  プロダクトチーム

  利用可能なAIモデルの確認や、クラスターのヘルス状態をリアルタイムで把握できます。

• 01

  How do I connect this MCP to my H2O.ai instance?

  You just need to provide your H2O.ai Base URL, which you can find in your H2O cluster settings or cloud dashboard, during the setup process.

• 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 monitor my cluster's hardware usage?

  Yes, you can use the cloud status capabilities to check hardware architecture health and memory utilization within your H2O instances.

• 04

  Is it possible to see the progress of training jobs?

  Yes, you can query the timeline of training jobs and tasks queued on your cluster to see exactly how they are progressing.

• 05

  Does this MCP work with H2O.ai cloud?

  Yes, it is designed to connect to your H2O.ai instances, including cloud-based clusters.

• 06

  Can my agent list all data frames currently loaded in my H2O cluster?

  Yes. Use the 'list_frames' capability. The agent retrieves the list of structured datasets securely loaded into memory, including their IDs and basic metadata, allowing you to browse available data flawlessly.

• 07

  How do I check the progress of a model training job via chat?

  Use the 'list_jobs' capability. Your agent will query the timeline nodes tracking all long-running tasks on the cluster, providing you with the current execution status and progress percentages synchronously.

• 08

  Can I see the internal architecture and metrics of a model through the agent?

  Absolutely. Use the 'get_model' capability with the specific model ID. The agent will fetch the detailed configuration blocks, exposing hyperparameters and performance metrics natively within your chat context.

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