Gpu
FreeNot checkedExposes local NVIDIA GPU (CUDA) and Rust-to-WASM toolchain as MCP tools for sovereign local compute.
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-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
Install Gpu in Claude Desktop, Claude Code & Cursor
unyly install gpu-mcpInstalls 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-mcpFAQ
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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