MCP server to run MATLAB code from LLM via the Matlab Engine API.
MATLAB MCP Integration MCP server is a locally run integration for AI assistants that speak the Model Context Protocol. MCP server to run MATLAB code from LLM via the Matlab Engine API.
This is an implementation of a Model Context Protocol (MCP) server for MATLAB. It allows MCP clients (like LLM agents or Claude Desktop) to interact with a shared MATLAB session using the MATLAB Engine API for Python.
Once MATLAB MCP Integration is connected, these are the calls the assistant has available:
Non — Blocking Execution:** MATLAB engine calls are run asynchronously using asyncio.to_thread to prevent blocking the serverYou will need one environment variable: MY_VAR. Keep credentials in your client's env block or a secrets manager rather than in a file you might commit.
numpy Python package.Setup follows the usual MCP pattern — install or clone the server, register it in your client's configuration file, restart the client.
This sits in the developer tooling group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. MATLAB MCP Integration's toolset — Non — is a fair guide to whether it matches your workflow. It is maintained by jigarbhoye04; worth a glance at recent repository activity before you build anything load-bearing on it.
This entry was verified against MATLAB MCP Integration's own documentation before publication; SyncDev keeps the directory reviewed rather than auto-generated.
| Tool | What it does |
|---|---|
| Non | Blocking Execution:** MATLAB engine calls are run asynchronously using asyncio.to_thread to prevent blocking the server. |
numpy Python package.| Variable | Description | Required |
|---|---|---|
| MY_VAR | Configuration value read at startup. | Optional |
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