Matlab Local Agent Quickstart — Data skill for Claude Code

MATLAB Local Agent Quickstart

Run a local AI coding agent against MATLAB®, with no code, data, or prompts sent off the machine.

This repository connects three pieces: a local LLM runtime, the [OpenCode](https://opencode.ai) coding agent, and the [MATLAB MCP Server](https://github.com/matlab/matlab-mcp-server) with settings tuned for local models, then verifies the result with five demos.

Requirements

• MATLAB R2025a or later (R2025a enables the plain-text Live Script format one demo produces)
• Git™
• The MATLAB MCP Server
• One local LLM runtime: Ollama, LM Studio, or llama.cpp
• One agentic coding tool: OpenCode
• Hardware per the tier table below

Step 1: Prepare

Get the repo:

git clone https://github.com/matlab/matlab-local-agent-quickstart.git

Then run the readiness check in MATLAB:

cd matlab-local-agent-quickstart/prepare
checkLocalAI

It detects your memory, GPU, MATLAB version, Git, and Node.js®, assigns your machine a tier, and prints the recommended model, quantization, context window, and harness. It makes no network calls.

Tier	Hardware	Recommended model	Context	Harness	Skills
Small	16 GB Apple® silicon; 12 GB NVIDIA® GPU	Gemma 4 12B QAT, Q4	8k-16k	OpenCode	off
Medium	32 GB+ Apple silicon; 24 GB+ NVIDIA GPU	Qwen3-Coder-30B-A3B, Q4_K_M	16k-32k	OpenCode	curated

Small tier supports single-step assisted help. Medium should be used for reliable autonomous work.

Step 2: Set Up

Follow one guide per piece, in order:

1. MATLAB MCP Server: download the binary and note its path.
2. Runtime: Ollama · LM Studio · [llama.cpp](docs/setup-llamacpp.