bionic-mcp
Allows using Apple's on-device Core AI / Neural Engine as a backend for running local models, with automatic fallback to LM Studio.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@bionic-mcpwhich models are currently loaded?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
bionic-mcp
You run models in LM Studio. bionic-mcp turns them into tools Claude Code (or any MCP client) can call, so you can hand the cheap and bulky work to your own machine. Free, local, private, nothing leaves your Mac.
You, in Claude Code: "classify these 50 log lines by severity"
↓
runs on your hardware, 0 API tokensInstall
git clone https://github.com/turner-moore/bionic-mcp.git && cd bionic-mcp && npm install && \
claude mcp add -s user bionic -- node "$(pwd)/index.js"Then start LM Studio's local server (that's where the models are):
~/.lmstudio/bin/lms server start{
"mcpServers": {
"bionic": {
"command": "node",
"args": ["/absolute/path/to/bionic-mcp/index.js"],
"env": { "BIONIC_BASE_URL": "http://127.0.0.1:1234" }
}
}
}Related MCP server: Local LLM MCP Server
Why not just point your client at the LM Studio API
Two things would eventually bite you. This server fixes both:
No silent model swaps. Ask LM Studio for a model that isn't loaded and its API quietly answers with whatever is loaded, so you think you're on a 14B and you're on a 3B. bionic-mcp refuses an unknown model id up front and checks response.model on every reply.
No surprise cold loads. On 16GB only one model stays resident, and switching costs 8-30s. model:"auto" uses whatever's already loaded, so a quick call stays quick.
Tools
Tool | Parameters | Does |
|
| Run a prompt on a local model. |
| none | List installed models with live load state and a capability card (quality, speed, context). |
Each prompt stands on its own. The local model can't see your Claude session, files, or memory, so inline every input and instruction it needs.
local.js is a second, optional server. It tries a faster on-device backend first (caix, Apple Core AI on the Neural Engine) and falls back to LM Studio when that's down.
claude mcp add -s user local -- node "$(pwd)/local.js"Requirements
Node 18+ (for built-in
fetch)LM Studio with its local server running
The capability card lives in
models.json, edit it to match your own installed models.
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