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PopNx MCPMCP servers for people who use AI · explained in plain words

Computegpu

by jysweeversion 1.2.1i★ –iComputer or cloud
Registry nameio.github.jyswee/computegpu

Install

Overview

Description from the maker (original English)

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

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Computer or cloud
  • Transport: stdio, Streamable HTTP, SSE
  • Category: Developer tools
  • You need to fill in: COMPUTEGPU_API_KEY, Authorization

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on the maker’s server: what you ask it goes through their server.
  • You fill in yourself: COMPUTEGPU_API_KEY, Authorization

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

  • Runs in the cloudNothing to install; it connects over the internet
  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Or run it on your computer

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "computegpu": {
      "command": "npx",
      "args": [
        "-y",
        "computegpu"
      ],
      "env": {
        "COMPUTEGPU_API_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add --transport http computegpu https://mcp.computegpu.com/mcp --header 'Authorization: your-value'

Or run it on your computer

claude mcp add computegpu --env COMPUTEGPU_API_KEY=your-value -- npx -y computegpu

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "computegpu": {
      "url": "https://mcp.computegpu.com/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

Or run it on your computer

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "computegpu": {
      "command": "npx",
      "args": [
        "-y",
        "computegpu"
      ],
      "env": {
        "COMPUTEGPU_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "computegpu": {
      "type": "http",
      "url": "https://mcp.computegpu.com/mcp",
      "headers": {
        "Authorization": "your-value"
      }
    }
  }
}

Or run it on your computer

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "computegpu": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "computegpu"
      ],
      "env": {
        "COMPUTEGPU_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This address needs a key in a request header, which the add-connector menu cannot set. Use Claude Code, Cursor or VS Code instead.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • COMPUTEGPU_API_KEY secret required env
    ComputeGpu API key (gpu_...). Get one with `npx computegpu signup you@example.com my-agent`; the owner verifies a card ($0, no charge) before the first deploy.
  • Authorization secret HTTP header
    Bearer gpu_... API key. Optional: without one the session starts in onboarding mode and computegpu_signup creates an account.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

We have not read this server’s tool list yet; we check endpoints in rotation.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 6, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account jyswee, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • … Not checked yet

    Endpoint responds

    Not checked yet; we check endpoints in rotation

  • … Not checked yet

    Sign-in with OAuth

    Not checked yet; we check endpoints in rotation

  • … Not checked yet

    No hidden instructions in tool descriptions

    Not checked yet; we read the tool list when we check the endpoint

Compared with others in Developer toolsi

  • More stars than 0% of the other 1385 servers in this category
  • Published to the registry more recently than 69% of the other 1385 servers in this category
  • Basic checks equal to or better than 100% of the other 1385 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Computegpu safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: COMPUTEGPU_API_KEY, Authorization

Does it run on my computer or in the cloud?

Either way works: install it on your computer or connect to the cloud version.

Is it still maintained?

The GitHub repo last changed –, and the latest version (1.2.1) reached the registry 20 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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

CommandDescription
signup Create account + get API key
login --key Save existing API key
logoutClear saved key
meShow account info
typesList 47 GPU models with pricing
cheapest --vram Find cheapest GPU for VRAM
deploy --gpu "RTX 4090"Deploy on-demand instance
podsList active instances
status Instance status + billing
stop Pause (billing stops)
resume Resume paused instance
destroy Permanent destroy
balanceWallet balance
topup 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)

Links

License

Proprietary. Copyright (c) 2026 Tyga.Cloud Ltd. See LICENSE.

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