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
| Registry | Package | Version | Transport |
|---|---|---|---|
| OCI image (Docker) | ghcr.io/pmady/gpu-mcp-server:v0.1.0 | — | stdio |
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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