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Gpu

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Exposes local NVIDIA GPU (CUDA) and Rust-to-WASM toolchain as MCP tools for sovereign local compute.

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About

Exposes local NVIDIA GPU (CUDA) and Rust-to-WASM toolchain as MCP tools for sovereign local compute.

README

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

tool what it does
probe_gpu Live nvidia-smi telemetry on the local machine
compile_kernel Compile a CUDA matmul kernel with nvcc (via MSVC vcvars64)
run_kernel Execute the compiled CUDA kernel on the local GPU, host-side timed
rust_build_wasm Compile a Rust crate to wasm32-unknown-unknown (local)
rust_run_wasm Run a .wasm via wasmtime if present; else report capability

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-agentmcp://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

from github.com/MYaelMendez/gpu-mcp

Install Gpu in Claude Desktop, Claude Code & Cursor

Recommended · one command, every IDE
unyly install gpu-mcp

Installs into Claude Desktop, Claude Code, Cursor & VS Code — handles npx, uvx and build-from-source repos for you.

First time? Get the CLI: curl -fsSL https://unyly.org/install | sh

Or configure manually

Run in your terminal:

claude mcp add gpu-mcp -- uvx --from git+https://github.com/MYaelMendez/gpu-mcp gpu-mcp

FAQ

Is Gpu MCP free?

Yes, Gpu MCP is free — one-click install via Unyly at no cost.

Does Gpu need an API key?

No, Gpu runs without API keys or environment variables.

Is Gpu hosted or self-hosted?

Self-hosted: the server runs locally on your machine via the install command above.

How do I install Gpu in Claude Desktop, Claude Code or Cursor?

Open Gpu on unyly.org, pick your client tab (Claude Desktop, Claude Code, Cursor) and press Install — the config is generated automatically, no JSON editing.

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