gpu-mcp

Sovereign local compute over the Model Context Protocol.

gpu-mcp is a zero-dependency (stdlib-only), air-gappable MCP server that exposes your local NVIDIA GPU (CUDA) and Rust → WASM toolchain to any MCP client — Claude Desktop, Cursor, gemini-cli, or Hermes Agent — as protocol-native tools. Nothing leaves the machine: the brain is a local model socket, the hands are local processes.

Canonical scheme (Hermes): ae://glocal-agent (alias +ae://cc, home://).

Tools

Related MCP server: mcp-gpu-server

Install

pip install gpu-mcp
# or, from source
git clone https://github.com/MYaelMendez/gpu-mcp && cd gpu-mcp
pip install -e .

Run the server

python -m gpu_mcp                 # stdio MCP server (register this with your client)
python -m gpu_mcp --self-test    # MCP handshake self-check (no GPU required)

Register with an MCP client

Point any MCP client at:

{
  "mcpServers": {
    "gpu-mcp": {
      "command": "python",
      "args": ["-m", "gpu_mcp"]
    }
  }
}

Works with Claude Desktop, Cursor, gemini-cli, and the Hermes Agent ae://glocal-agent surface.

Hermes Agent integration

gpu-mcp is a first-party primitive of the Hermes Agent sovereign stack. In hermes-fork, the VS Code extension bundles it and the conductor resolves ae://glocal-agent → mcp://gpu-mcp. This repo is the canonical, standalone, pip-installable source of truth.

Tests

pytest                              # MCP handshake + offline hands
python -m gpu_mcp --self-test     # quick in-process handshake check

GPU/wasm tool tests exercise real nvidia-smi, nvcc, and cargo when present; they fail loud (not silent) when the local toolchain is missing.

Why

Cloud agents can't give you your own GPU. gpu-mcp is the command-&-control surface for a bounded, offline local agent — your silicon, your weights, your rules. #opensourceware #hermiphicationisinevitable

MIT — © Yael Mendez · æ.store