# CloudGPU MCP (npm · cloudgpu-mcp)

Rent a per-minute GPU from your MCP client, run a job, download results, shut it down.

- Trust score: 79/100 (medium)
- Change this week: +4
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-11-05

## Components

- npm · `cloudgpu-mcp`: 79/100 (this document), [markdown](https://verifymcp.io/servers/mrhy7176-cloudgpu-mcp/cloudgpu-mcp.md), [page](https://verifymcp.io/servers/mrhy7176-cloudgpu-mcp/cloudgpu-mcp)

## Channel facts

- Registry: `npm`
- Package: `cloudgpu-mcp`
- Version: `0.3.0`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-11-05.

- **Supply Chain Security**: 81/100
  - No malware found by supply-chain analysis.
  - CVE check failed: a known high-severity CVE affects zod 3.25.76, a direct dependency. A fixed version is available.
  - No install/post-install scripts declared.
  - 34 of 100 dependencies flagged as unhealthy.
- **Provenance & Transparency**: 97/100
  - Source repository is publicly reachable at the declared URL.
  - Cryptographically verified build provenance (signed, bound to mrhy7176/cloudgpu-mcp).
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 1 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 80/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (good).
  - Tool/resource definitions use about 1303 tokens (~93/item across 14 items; 13 tools + 1 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 30/100
  - Stability observed for 9 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 83/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 48% of tool parameters carry a description.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - All 1 tool(s) whose name or description implies an irreversible operation declare an MCP destructiveHint annotation.
  - An AI judge read all 15 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### How do I install the CloudGPU MCP server?

CloudGPU MCP runs locally as an npm package, launched with npx -y cloudgpu-mcp. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add mrhy7176-cloudgpu-mcp -- npx -y cloudgpu-mcp
```

### Cursor

```json
{
  "mcpServers": {
    "mrhy7176-cloudgpu-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "cloudgpu-mcp"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "mrhy7176-cloudgpu-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "cloudgpu-mcp"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add mrhy7176-cloudgpu-mcp -- npx -y cloudgpu-mcp
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "mrhy7176-cloudgpu-mcp": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "cloudgpu-mcp"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add mrhy7176-cloudgpu-mcp --command npx --arg -y --arg cloudgpu-mcp
```

### Hermes

```yaml
mcp_servers:
  mrhy7176-cloudgpu-mcp:
    command: "npx"
    args: ["-y", "cloudgpu-mcp"]
```

### Netclaw

```json
{
  "McpServers": {
    "mrhy7176-cloudgpu-mcp": {
      "Transport": "stdio",
      "Command": "npx",
      "Arguments": [
        "-y",
        "cloudgpu-mcp"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add mrhy7176-cloudgpu-mcp -t stdio -c npx -a -y cloudgpu-mcp
```

### Other

```json
{
  "mcpServers": {
    "mrhy7176-cloudgpu-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "cloudgpu-mcp"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-11-04 (score 79, +6)

- [security regression] Known CVEs: unverified → fail
- [functional improvement] Dependency health: unverified → 0.84

### 2026-11-03 (score 73, +11)

- [security regression] Known CVEs: fail → unverified
- [security improvement] Malware scan: unverified → pass
- [functional regression] Dependency health: 0.84 → unverified
- [functional] Package version: 0.1.2 → 0.3.0
- [functional] Package version: 0.1.2 → 0.2.0

### 2026-11-02 (score 62, −15)

- [security regression] Malware scan: pass → unverified
- [functional] Package version: 0.1.1 → 0.1.2

### 2026-11-01 (score 77, +1)

- [functional regression] Security disclosure: unverified → fail

### 2026-10-31 (score 76, +1)

- [functional regression] Security disclosure: fail → unverified
- [functional improvement] Stability: unverified → 0.13
- [functional] Package version: 0.1.0 → 0.1.1

### 2026-10-28 (score 75, +15)

- [security improvement] Malware scan: unverified → pass

### 2026-10-27 (score 60)

First indexed and scored.

## MCP tools (13)

### `get_account` (~29 tokens)

CloudGPU account

Balance in USD, how many instances this account may run at once, and how many are running now.

### `list_gpus` (~90 tokens)

List GPUs

GPU models you can rent now, with VRAM, live price per GPU-hour in USD and availability (ok / low / none). Prices are live; never assume them.

Input parameters:

- `gpu_model` (string): Filter by name, e.g. 4090, A100, H20
- `min_vram_gb` (number): Only GPUs with at least this much VRAM per card

### `list_templates` (~51 tokens)

List templates

Ready-made instance images (e.g. JupyterLab, Ollama, ComfyUI, LLaMA-Factory) with the GPU each recommends. Templates with has_api_endpoint get a public HTTPS api_url.

### `estimate_cost` (~105 tokens)

Quote a rental

Live price and estimated cost for a GPU, plus your balance after it. Returns a quote_id that create_instance needs. Show the quote to the user and get an explicit yes before renting.

Input parameters:

- `gpu_count` (integer)
- `gpu_model` (string, required): GPU model exactly as list_gpus returns it
- `hours` (number, required): Expected run time in hours
- `template` (string): Template id from list_templates; omit for a plain GPU with Python and CUDA

### `list_models` (~49 tokens)

List hosted models

Models on CloudGPU's OpenAI-compatible API (same key, same balance). Use them from code with base_url https://cloudgpu.app/v1 instead of renting a GPU when you only need inference.

### `get_status` (~55 tokens)

Instance status

Status (creating / running / stopped / failed), minutes run, cost so far, whether SSH is ready, the public api_url if the template has one, and the auto-shutdown limits.

Input parameters:

- `instance_id` (string, required)

### `list_instances` (~30 tokens)

List instances

Instances on this account: running, starting, and those stopped in the last 7 days, with cost.

### `create_instance` (~252 tokens)

Rent a GPU

Rents the GPU from a quote. Costs money. Requires a quote_id from estimate_cost that the user has approved. max_spend_usd and max_hours are enforced by CloudGPU's servers: the instance is destroyed when either is reached, even if this assistant has disconnected. idle_minutes destroys it after the GPU sits idle that long (installing packages and downloading data count as idle, so allow for setup). setup_script (optional bash) runs once as root after the instance is handed over; its output is in /root/cloudgpu-setup.log.

Input parameters:

- `idle_minutes` (integer): Destroy after the GPU has been idle this long; 0 turns it off; otherwise at least 10
- `max_hours` (number, required): Hard time limit in hours (at most 24)
- `max_spend_usd` (number, required): Budget for this instance in USD (at most 50)
- `quote_id` (string, required)
- `setup_script` (string): Optional bash script run once as root in the background after the instance is handed over; output in /root/cloudgpu-setup.log
- `user_confirmed` (boolean, required): true only if the user explicitly approved this quote in the conversation

### `run_command` (~122 tokens)

Run a command on the instance

Runs a bash command on the instance as root, in an interactive-style shell so conda/venv from ~/.bashrc are active. Foreground returns the exit code and the last 20k characters of output. For anything longer than a few minutes (training, big downloads) use background=true, then tail_logs.

Input parameters:

- `background` (boolean)
- `command` (string, required): bash command or script
- `instance_id` (string, required)
- `timeout_sec` (integer): Foreground only
- `workdir` (string): Directory to run in

### `upload` (~108 tokens)

Upload to the instance

Copies a local file or directory (this computer) to the instance over SFTP. node_modules, .git and __pycache__ are skipped. Credentials files (.ssh, .env, keys) are refused unless allow_sensitive is true and the user asked for it.

Input parameters:

- `allow_sensitive` (boolean)
- `instance_id` (string, required)
- `local_path` (string, required)
- `remote_path` (string, required): Destination on the instance, e.g. /root/project or /root/data/

### `download` (~71 tokens)

Download from the instance

Copies a file or directory from the instance to this computer. Do this for every result before stop_instance: destroying an instance erases its disk.

Input parameters:

- `instance_id` (string, required)
- `local_path` (string, required): Local destination file or directory, e.g. ./outputs/
- `remote_path` (string, required)

### `tail_logs` (~75 tokens)

Job logs and GPU use

Last lines of a background job's log (job_id) or any log file (path), whether the job is still running and its exit code, plus current GPU utilisation and memory.

Input parameters:

- `instance_id` (string, required)
- `job_id` (string)
- `lines` (integer)
- `path` (string)

### `stop_instance` (~68 tokens)

Destroy an instance

Destroys the instance and stops billing. Its disk is erased. If commands were run on it in this session and nothing was downloaded, this refuses unless force=true (only after the user confirms the results are not needed).

Input parameters:

- `force` (boolean)
- `instance_id` (string, required)

## Diagnostics

Captured diagnostic sections: Provenance, Vulnerabilities, Dependencies. The full working is on the page: https://verifymcp.io/servers/mrhy7176-cloudgpu-mcp/cloudgpu-mcp#diagnostics

## Score history

- 2026-11-05: 79
- 2026-11-04: 79
- 2026-11-03: 73
- 2026-11-02: 62
- 2026-11-01: 77
- 2026-10-31: 76
- 2026-10-30: 75
- 2026-10-29: 75
- 2026-10-28: 75
- 2026-10-27: 60

## Common questions

### What is the CloudGPU MCP server?

CloudGPU MCP is listed in the public MCP registry as io.github.mrhy7176/cloudgpu-mcp. Rent a per-minute GPU from your MCP client, run a job, download results, shut it down. This page covers its npm package (cloudgpu-mcp).

### Is the CloudGPU MCP server safe to use?

CloudGPU MCP scores 79 out of 100 on VerifyMCP. We recorded 1 known advisory against it as of 5 November 2026. It declares no install or post-install scripts. Its build provenance is signed and verified. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the CloudGPU MCP server expose?

CloudGPU MCP exposes 13 tools: get_account, list_gpus, list_templates, estimate_cost, list_models, and 8 more. Their descriptions and schemas cost roughly 1,105 tokens of context every time the server is loaded.

### Is the CloudGPU MCP server still maintained?

CloudGPU MCP is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What licence is the CloudGPU MCP server under?

CloudGPU MCP declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

## Links

- npm package: https://www.npmjs.com/package/cloudgpu-mcp
- Socket report: https://socket.dev/npm/package/cloudgpu-mcp
- Repository: https://github.com/mrhy7176/cloudgpu-mcp
- Website: https://cloudgpu.app/docs/mcp
- Changelog RSS feed: https://verifymcp.io/servers/mrhy7176-cloudgpu-mcp/cloudgpu-mcp.xml
- Changelog JSON feed: https://verifymcp.io/servers/mrhy7176-cloudgpu-mcp/cloudgpu-mcp.json
- HTML version of this page: https://verifymcp.io/servers/mrhy7176-cloudgpu-mcp/cloudgpu-mcp