What is io.github.jyswee/computegpu?

Rent cloud GPUs from your agent: live catalogue, deploy, stop, destroy. Per-second billing.

How do I install io.github.jyswee/computegpu?

Install io.github.jyswee/computegpu via npm from https://registry.npmjs.org, then add the server config to your MCP client (Claude Desktop, Cursor, or VS Code).

Is io.github.jyswee/computegpu open source?

Yes, io.github.jyswee/computegpu is open source under the NOASSERTION license. Source code is available at https://github.com/jyswee/computegpu-cli.

What category does io.github.jyswee/computegpu belong to?

io.github.jyswee/computegpu is listed under Cloud Providers MCP servers on MCPFind.

io.github.jyswee/computegpu — MCP Server for Cloud Providers

computegpu

Rent cloud GPUs from your terminal. Deploy in 30 seconds.

npm i -g computegpu
computegpu signup you@company.com my-agent
computegpu deploy --gpu "RTX 4090"

Install

npm i -g computegpu

Requires Node.js 18+.

Quick Start

# Create account
computegpu signup you@company.com my-project

# Browse GPUs
computegpu types

# Deploy
computegpu deploy --gpu "RTX 4090" --models llama3.3

# Check status
computegpu pods
computegpu status POD_ID

# Stop
computegpu stop POD_ID

Commands

Command	Description
`signup <email> <tenantId>`	Create account + get API key
`login --key <KEY>`	Save existing API key
`logout`	Clear saved key
`me`	Show account info
`types`	List 47 GPU models with pricing
`cheapest --vram <GB>`	Find cheapest GPU for VRAM
`deploy --gpu "RTX 4090"`	Deploy on-demand instance
`pods`	List active instances
`status <podId>`	Instance status + billing
`stop <podId>`	Pause (billing stops)
`resume <podId>`	Resume paused instance
`destroy <podId>`	Permanent destroy
`balance`	Wallet balance
`topup <amount>`	Request top-up ($1 minimum)

Deploy Options

computegpu deploy --gpu "RTX 4090"           # on-demand
computegpu deploy --gpu "RTX 4090" --spot    # 50% off (preemptible)
computegpu deploy --gpu "H100" --count 4     # multi-GPU
computegpu deploy --gpu "RTX 4090" --models llama3.3,gemma4  # pre-load models
computegpu deploy --gpu "RTX 4090" --type docker  # Docker + SSH
computegpu deploy --gpu "RTX 4090" --volume 100   # persistent storage

Config

API key is saved to ~/.computegpu/config.json (global) or ./.computegpu/config.json (local).

Priority: --key flag > COMPUTEGPU_API_KEY env > local config > global config.

computegpu login --key gpu_your_key          # save globally
computegpu login --key gpu_your_key --local  # save per-project
computegpu config                             # show active config

Pricing

47 GPU models. Per-second billing. $1 minimum top-up.

Consumer: RTX 3060 ($0.22/hr) to RTX 5090 ($1.24/hr)
Datacenter: A40 ($0.64/hr) to H200 ($10.76/hr)
Spot: 50% off (preemptible with 5-min warning)

License

Set up in your AI client

AI clientOperating system

Merge this template into ~/Library/Application Support/Claude/claude_desktop_config.json. Keep existing servers. Add any arguments, credentials, and permissions required by the maintainer; this template has not been install-tested.

json

{
  "mcpServers": {
    "io-github-jyswee-computegpu": {
      "command": "npx",
      "args": [
        "-y",
        "computegpu"
      ]
    }
  }
}

Restart Claude Desktop completely for changes to take effect. Confirm the server appears connected in the client’s tool list, then try a read-only example from its documentation.

Claude Desktop setup reference

Compatible MCP Clients

io.github.jyswee/computegpu works with any MCP-compatible client. Copy the config snippet from the Configuration section above and add it to the file shown for your client, then restart the application.

Claude Desktop~/Library/Application Support/Claude/claude_desktop_config.jsonRestart Claude Desktop completely for changes to take effect.

Cursor~/.cursor/mcp.jsonRestart Cursor for changes to take effect.

VS Code.vscode/mcp.jsonReload VS Code window for changes to take effect.

Windsurf~/.codeium/windsurf/mcp_config.jsonRestart Windsurf for changes to take effect.

Claude Code.mcp.jsonSave at the project root, then start Claude Code in that project and review the MCP server approval prompt. Keep real credentials out of shared files.

io.github.jyswee/computegpu