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ClaudeChatGPTPerplexityGeminiMicrosoft CopilotRaycastMeta AIGrokZ.aiQwenKimi
DeepSeekMistralCursorVS CodeWindsurfJetBrainsClineLovableVercel AI SDKLangChain

Use RunPod API with your AI.

Connect your account once and let the AI you already use work with it, without building another integration. Integrate your AI securely to RunPod to cleanly quickly provision scalable GPU pods, manage active instances, and inspect serverless endpoints and custom templa

Included with plan

Ask AI about this Connector

Developed, maintained, and hosted by Vinkius.

MCP VERIFIED · PRODUCTION READY · VINKIUS GUARANTEED

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Works with modern AI clients that support MCP, including ChatGPT, Claude, Cursor, and more.

ChatGPTClaudeCursorPerplexityGeminiMicrosoft CopilotRaycastMeta AI

Complete set · 7 capabilities

The complete RunPod API capability set.

These are the exact actions your AI can choose when you ask it to work with RunPod API.

Capability set01 / 02

01-04

4 capabilities in this set.

Part of 7 available through RunPod API.

  1. 01

    Create pod

    Specify name, GPU type, and Docker image. Creates a new GPU pod

  2. 02

    List endpoints

    Lists all serverless endpoints

  3. 03

    List gpu types

    Lists available GPU hardware types

  4. 04

    List pods

    Lists all GPU pods in the account

Capability set02 / 02

05-07

3 capabilities in this set.

Part of 7 available through RunPod API.

  1. 05

    List templates

    Lists saved pod templates

  2. 06

    Get pod

    Retrieves details for a specific GPU pod

  3. 07

    Stop pod

    Stops a running GPU pod

Observed, not estimated

863ms average. Fast in production.

RunPod API is checked daily against the live service.

Daily averagePeak 1149ms
Aug 20Today
Fastest day
704ms
Slowest day
1149ms
14-day trend
Stable-1%

Connect your client

One URL. Every client.

Activate the Connector, copy your link, and paste it into the client you already use. 7 capabilities arrive ready to run.

Preview access · not provider authentication

The vk_preview_* token belongs to Vinkius preview infrastructure. It lets Claude discover and display the capabilities of RunPod API, so you can see the experience inside your AI.

It does not authenticate your account with RunPod API. Actions requiring credentials or live account data may not run until you activate the Connector and authorize the service.

RunPod API Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_mqfmppnjNgzd7DnF3DKymtiD5h0tXpOI6WsCj5ji/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  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.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "runpod-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_mqfmppnjNgzd7DnF3DKymtiD5h0tXpOI6WsCj5ji/mcp"
    }
  }
}
  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Step-by-step instructions for each client are in the guide. How to connect

FAQ

Questions RunPod API owners ask.

  • 01

    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.

  • 02

    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.

  • 03

    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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