RunPod MCP Server

This Model Context Protocol (MCP) server enables you to interact with the RunPod REST API through Claude or other MCP-compatible clients.

- Pods: Create, list, get details, update, start, stop, and delete pods
- Endpoints: Create, list, get details, update, and delete serverless endpoints
- Templates: Create, list, get details, update, and delete templates
- Network Volumes: Create, list, get details, update, and delete network volumes
- Container Registry Authentications: Create, list, get details, and delete authentications

- Node.js 18 or higher
- A RunPod account and API key
- Claude for Desktop or another MCP-compatible client

To install runpod-mcp-ts for Claude Desktop automatically viaSmithery:

npx -y @smithery/cli install @runpod/runpod-mcp-ts --client claude

npm install

# Linux/macOS export RUNPOD_API_KEY=your_api_key_here # Windows (Command Prompt) set RUNPOD_API_KEY=your_api_key_here # Windows (PowerShell) $env:RUNPOD_API_KEY="your_api_key_here"

You can get your API key from theRunPod console.
- Open Claude for Desktop
- Edit the config file:~/Library/Application Support/Claude/claude_desktop_config.json(macOS) or%APPDATA%\Claude\claude_desktop_config.json(Windows)
- Add the server configuration:

{ "mcpServers": { "runpod": { "command": "node", "args": ["/path/to/runpod-mcp-server/build/index.js"], "env": { "RUNPOD_API_KEY": "your_api_key_here" } } } }

Make sure to replace the"args": ["/path/to/runpod-mcp-server/build/index.js"]with the path to the build folder in the repository.

Here are some examples of how to use the server with Claude:

Create a new RunPod pod with the following specifications: - Name: test-pod - Image: runpod/pytorch:2.1.0-py3.10-cuda11.8.0-devel-ubuntu22.04 - GPU Type: NVIDIA GeForce RTX 4090 - GPU Count: 1

Create a RunPod serverless endpoint with the following configuration: - Name: my-endpoint - Template ID: 30zmvf89kd - Minimum workers: 0 - Maximum workers: 3

This server requires your RunPod API key, which grants full access to your RunPod account. For security:

- Never share your API key
- Be cautious about what operations you perform
- Consider setting up a separate API key with limited permissions
- Don't use this in a production environment without proper security measures

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