MATLAB AI Model Deployment

by matlab

MATLAB AI Model Deployment is a DevOps skill for Claude Code, published by matlab in matlab-agentic-toolkit.

938 stars115 forkson matlab/matlab-agentic-toolkitAdded 2026/08/21+2% in starsRepository updated 2026/08/13

View source on GitHub Download repo ZIP

agent-skillsclaude-codecodex-pluginengineering-agentsgithub-copilotmatlabmatlab-mcp-server

Install in seconds

Install MATLAB AI Model Deployment

Copy MATLAB AI Model Deployment into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/matlab/matlab-agentic-toolkit/tree/main/skills-catalog/code-generation/matlab-deploy-ai-model ~/.claude/skills/matlab-deploy-ai-model

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/matlab/matlab-agentic-toolkit.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills-catalog/code-generation/matlab-deploy-ai-model/SKILL.md in matlab/matlab-agentic-toolkit
Installs to: ~/.claude/skills/matlab-deploy-ai-model
Collection: One of 25 skills cataloged from this repository
Category: DevOps — 798 skills

What MATLAB AI Model Deployment does

MATLAB AI Model Deployment generates MEX, C/C++, or CUDA code from PyTorch ExportedProgram or LiteRT models for use in applications or Simulink. Use it when you need to verify inference in MATLAB and then deploy the model as a library, executable, or GPU-accelerated build.

MATLAB AI Model Deployment is cataloged under DevOps on DirSkills. MATLAB AI Model Deployment comes from a repository tagged agent-skills, claude-code, codex-plugin, engineering-agents and github-copilot.

Documentation

README

Excerpt

Generate C/C++/CUDA Code from an AI Model

Generate deployable C/C++ or CUDA code from an AI model using MATLAB Coder or GPU Coder. The workflow follows a common pattern regardless of model framework: load, inspect, write entry-point, generate MEX, verify, then generate production code.

When to Use

User wants to generate C/C++/CUDA code from an AI model (PyTorch, LiteRT)
User has a model file (.pt2, .tflite) and wants to load it into MATLAB
User wants MEX acceleration for an AI model
User wants to generate CUDA code or GPU-accelerated MEX from an AI model
User wants to deploy an AI model to hardware
User wants to use a PyTorch or LiteRT model in Simulink (simulation or code generation)
User wants to verify AI model numerics between the source framework and MATLAB

This is the opening of the README. Read the full README on GitHub.

Frequently asked about MATLAB AI Model Deployment

What else does matlab publish alongside MATLAB AI Model Deployment?
MATLAB AI Model Deployment is one of 25 skills that DirSkills catalogs from matlab/matlab-agentic-toolkit, the repository it ships in. Its siblings there include Aerospace Fundamentals, Build RoadRunner Scenario From OpenSCENARIO and Compute Aerospace Environment. Each one is a separate skill with its own page in this directory, installs the same way MATLAB AI Model Deployment does, and is maintained by matlab in that same repository. The rest of the collection is listed on the matlab/matlab-agentic-toolkit page.
How does MATLAB AI Model Deployment compare to other DevOps skills?
MATLAB AI Model Deployment ranks #484 by stars among the 798 DevOps skills in this catalog. The most-starred ones next to it are Backend Patterns, API Connector Builder and Migration. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of MATLAB AI Model Deployment against them. Open each page to compare what they document and how they install.