Developer · Local MCP server

GPU MCP Server

NVIDIA GPU metrics as MCP tools — utilization, memory, temperature, power. Supports MIG.

What the MCP Registry states

The entry as published to the official MCP Registry (read 2026-10-04), latest version.

Registry name
io.github.pmady/gpu-mcp-server
Version
0.1.0
Status
Active
Category
developer
Transport
stdio (local process)
Package
OCI image (Docker)
Published
2026-06-25
Updated
2026-06-25
Publisher
pmady (GitHub)
Repository
github.com/pmady/gpu-mcp-server
Source
Registry API entry

Packages

RegistryPackageVersionTransportEnvironment variables
OCI image (Docker)ghcr.io/pmady/gpu-mcp-server:v0.1.0—stdioNone declared

How to connect GPU MCP Server

GPU MCP Server runs locally from a container image in an OCI registry such as Docker Hub or GitHub Container Registry: ghcr.io/pmady/gpu-mcp-server:v0.1.0. It speaks MCP over stdio, so the client starts it as a program and talks to it through standard input and output. It needs Docker or another OCI container runtime; started with docker run — the usual command is docker run -i --rm ghcr.io/pmady/gpu-mcp-server:v0.1.0.

In the mcpServers JSON format that many desktop and editor MCP clients read, the entry looks like this (placeholders in angle brackets):

{
  "mcpServers": {
    "gpu-mcp-server": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/pmady/gpu-mcp-server:v0.1.0"
      ]
    }
  }
}

Derived from the registry entry, not tested here. What the server does, and on what terms, is set by its publisher; check its repository or website before giving it access to your accounts or files. How to add an MCP server to an assistant · Before you connect

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