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MATLAB MCP Integration

@jigarbhoye04

Repository

Basic information

Category

Developer Tools

License

MIT

Transports

stdio

Author

jigarbhoye04

About MATLAB MCP Integration

MCP server to run MATLAB code from LLM via the Matlab Engine API.

#mcp#matlab#claude#llm#mcp-server

MATLAB MCP Integration config

Add this server to your MCP-compatible client using the configuration below.

{
  "mcpServers": {
    "MatlabMCP": {
      "command": "uv",
      "args": [
        "init"
      ]
    }
  }
}

MATLAB MCP Integration tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MATLAB MCP Integration?

This is an MCP (Model Context Protocol) server that enables MCP clients—such as LLM agents or Claude Desktop—to interact directly with a shared MATLAB session. It uses the MATLAB Engine API for Python to execute MATLAB code, retrieve workspace variables, and return structured JSON results.

How to use MATLAB MCP Integration?

Install the server by cloning the repository, setting up a Python virtual environment (recommended with uv), and installing dependencies. Then start MATLAB and run matlab.engine.shareEngine to make the engine available. Finally, configure the MCP client (e.g., Claude Desktop) by editing its claude_desktop_config.json to point to the uv runner and the server’s main.py script. Tools exposed are runMatlabCode (execute arbitrary MATLAB code) and getVariable (retrieve workspace variables).

Key features of MATLAB MCP Integration

  • Execute arbitrary MATLAB code via the runMatlabCode tool.
  • Retrieve workspace variables with the getVariable tool.
  • Returns results and errors as structured JSON.
  • Non‑blocking execution using asyncio.to_thread.
  • Standard logging to stderr for client visibility.
  • Connects to an existing shared MATLAB session.

Use cases of MATLAB MCP Integration

  • Interactive data analysis and visualization from a chat interface.
  • Automated generation of MATLAB scripts and figures via an LLM.
  • Coupling MATLAB’s numerical computation with AI‑driven workflows.
  • Rapid prototyping without leaving the MCP client environment.

Frequently asked questions

1

What are the requirements to run MATLAB MCP Integration?

Python 3.12 or higher, MATLAB (**R2023a or higher recommended**) with the MATLAB Engine API for Python installed, and the `numpy` Python package.

2

How do I share the MATLAB engine so the server can connect?

In the MATLAB Command Window, run `matlab.engine.shareEngine`. Verify with `matlab.engine.isEngineShared`, which should return `true` or `1`.

3

How do I configure MATLAB MCP Integration with Claude Desktop?

Edit `claude_desktop_config.json` and add an entry under `mcpServers` with the command set to your `uv` executable, `args` containing `["--directory", "<absolute-path-to-repo>", "run", "main.py"]`. Use absolute paths and restart Claude Desktop.

4

What tools does the server provide?

Two tools: `runMatlabCode` to execute any MATLAB code, and `getVariable` to fetch the value of a variable from the MATLAB workspace. Both return structured JSON.

5

Where can I find more detailed documentation?

The repository contains an `Updates.md` file in the `Docs/` folder with detailed documentation on features, usage, and development notes. A DeepWiki page is also linked in the README.

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