RunpodをChatGPT、Claude、Geminiに接続

• 01 / 03エンドポイントの監査方法
• 02 / 03Podの監視と停止について
• 03 / 03GPUポッドのプロビジョニング方法

最速日

691ms

最遅日

1111ms

14日間の傾向

改善傾向-5%

RunPod API 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_mqfmppnjNgzd7DnF3DKymtiD5h0tXpOI6WsCj5ji/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 — RunPod API capabilities are ready to use.

設定 · claude_desktop_config.jsonコピー

{
  "mcpServers": {
    "runpod-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_mqfmppnjNgzd7DnF3DKymtiD5h0tXpOI6WsCj5ji/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？ RunPod API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

  DevOpsエンジニア

  Webダッシュボードを切り替えることなく、チャットインターフェースから直接、大規模なワークロードのプロビジョニングや監査を行いたい方。

• 02

  AI開発者

  自然言語によるリクエストを通じて、高出力なサーバーレスLLMの実装を効率的に管理したい方。

• 01

  How do I connect my RunPod account?

  You need to generate an API Key in your RunPod settings with Read/Write permissions and then add that key to the MCP connection module.

• 02

  Can I stop pods to save money?

  Yes. You can tell your agent to stop a specific pod by its ID to halt active billing.

• 03

  What kind of hardware can I deploy?

  The MCP can list all available GPU types and templates, allowing you to choose the specific architecture you need for your workload.

• 04

  Is this compatible with my existing AI capabilities?

  Yes, this MCP works with any MCP-compatible client like Claude, Cursor, or Windsurf.

• 05

  Can I manage serverless functions?

  Yes, the MCP includes a capability to list all your registered serverless endpoints.

• 06

  Can the AI forcefully terminate or delete critical production endpoint fleets on demand?

  No. This module safely allows the AI to only pause and manage running instances. Destructive deletion actions (like completely erasing a pod) are intentionally prohibited by the tooling design to protect your critical compute resources from unintended loss.

• 07

  Can the AI provision large GPU arrays automatically?

  Yes. Using the create_pod capability, the AI can query the available hardware models (such as A100 or H100) and immediately launch new Docker clusters based on existing community templates, simplifying complex DevOps scaling actions significantly.

• 08

  Will the AI know the billing state or the real-time cost of running each endpoint?

  No. The current RunPod AI module is concentrated on operational control and system orchestration, such as discovering inactive processes and booting new instances. Deep billing analytics or invoice extraction is not natively integrated in the commands exposed to the AI at this time.

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