# GPU Server (pypi · gpu-server)

MCP server for GPU monitoring: nvidia-smi, VRAM, utilization, temperature

- Trust score: 69/100 (medium)
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-10-22

## Components

- pypi · `gpu-server`: 69/100 (this document), [markdown](https://verifymcp.io/servers/moezdil-mcp-gpu-server/gpu-server.md), [page](https://verifymcp.io/servers/moezdil-mcp-gpu-server/gpu-server)

## Channel facts

- Registry: `pypi`
- Package: `gpu-server`
- Version: `0.2.2`
- 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 2026-10-22.

- **Supply Chain Security**: 100/100
  - No malware found by supply-chain analysis.
  - No known CVEs affecting this package version or its production dependencies.
  - No install/post-install scripts declared.
  - 1 of 29 dependencies flagged as unhealthy.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 0 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 65/100
  - AI-judged instruction clarity (good).
  - Tool/resource definitions use about 108 tokens (~21/item across 5 items; 5 tools + 0 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 3/100
  - Stability observed for 1 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 5 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 5 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).

## Install

### How do I install the GPU Server MCP server?

GPU Server runs locally as a PyPI package, launched with uvx gpu-server. 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 moezdil-mcp-gpu-server -- uvx gpu-server
```

### Cursor

```json
{
  "mcpServers": {
    "moezdil-mcp-gpu-server": {
      "command": "uvx",
      "args": [
        "gpu-server"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "moezdil-mcp-gpu-server": {
      "command": "uvx",
      "args": [
        "gpu-server"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add moezdil-mcp-gpu-server -- uvx gpu-server
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "moezdil-mcp-gpu-server": {
      "type": "local",
      "command": [
        "uvx",
        "gpu-server"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add moezdil-mcp-gpu-server --command uvx --arg gpu-server
```

### Hermes

```yaml
mcp_servers:
  moezdil-mcp-gpu-server:
    command: "uvx"
    args: ["gpu-server"]
```

### Netclaw

```json
{
  "McpServers": {
    "moezdil-mcp-gpu-server": {
      "Transport": "stdio",
      "Command": "uvx",
      "Arguments": [
        "gpu-server"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add moezdil-mcp-gpu-server -t stdio -c uvx -a gpu-server
```

### Other

```json
{
  "mcpServers": {
    "moezdil-mcp-gpu-server": {
      "command": "uvx",
      "args": [
        "gpu-server"
      ]
    }
  }
}
```

## 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.

### 2026-10-22 (score 69, +30)

- [security improvement] Injection markers: unverified → pass
- [security] First check of Judged manipulation: pass
- [functional improvement] Tool coverage: unverified → 100
- [functional improvement] MCP protocol: unverified → pass
- [functional improvement] Stability: unverified → 0.03
- [functional] First check of Schema quality: fail
- [functional] First check of Destructive annotations: pass
- [functional] First check of Schema quality: pass
- [functional] First check of Schema quality: good
- [functional] First check of Tool coverage: 100

### 2026-10-21 (score 39)

First indexed and scored.

## MCP tools (5)

### `gpu_info` (~21 tokens)

GPU name, driver version, and CUDA version for each device.

### `gpu_utilization` (~19 tokens)

GPU core and memory utilization percentage for each device.

### `gpu_vram` (~27 tokens)

VRAM total, used, free (MiB) and utilization % for each device.

### `gpu_temperature` (~17 tokens)

Core temperature in °C for each device.

### `gpu_stats` (~24 tokens)

Full snapshot: info, VRAM, utilization, and temperature for every device.

## Diagnostics

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

## Score history

- 2026-10-22: 69
- 2026-10-21: 39

## Common questions

### What is the GPU Server MCP server?

GPU Server is an MCP server listed in the public MCP registry as io.github.moezdil/mcp-gpu-server. MCP server for GPU monitoring: nvidia-smi, VRAM, utilization, temperature. This page covers its PyPI package (gpu-server).

### Is the GPU Server MCP server safe to use?

GPU Server scores 69 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 22 October 2026. It declares no install or post-install scripts. 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 GPU Server MCP server expose?

GPU Server exposes 5 tools: gpu_info, gpu_utilization, gpu_vram, gpu_temperature, gpu_stats. Their descriptions and schemas cost roughly 108 tokens of context every time the server is loaded.

### Is the GPU Server MCP server still maintained?

GPU Server is still listed as active in the MCP registry. We last reached this channel on 22 October 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 GPU Server MCP server under?

GPU Server 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

- PyPI project: https://pypi.org/project/gpu-server/
- Socket report: https://socket.dev/pypi/package/gpu-server
- Repository: https://github.com/moezdil/mcp-gpu-server
- Changelog RSS feed: https://verifymcp.io/servers/moezdil-mcp-gpu-server/gpu-server.xml
- Changelog JSON feed: https://verifymcp.io/servers/moezdil-mcp-gpu-server/gpu-server.json
- HTML version of this page: https://verifymcp.io/servers/moezdil-mcp-gpu-server/gpu-server