by matlab
The Simulink Agentic Toolkit gives your AI agent both the tools and the expertise to work effectively with Simulink and Model-Based Design.
# Add to your Claude Code skills
git clone https://github.com/matlab/simulink-agentic-toolkitGuides for using ai agents skills like simulink-agentic-toolkit.
Last scanned: 5/23/2026
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}simulink-agentic-toolkit is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by matlab. The Simulink Agentic Toolkit gives your AI agent both the tools and the expertise to work effectively with Simulink and Model-Based Design. It has 848 GitHub stars.
Yes. simulink-agentic-toolkit passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/matlab/simulink-agentic-toolkit" and add it to your Claude Code skills directory (see the Installation section above).
simulink-agentic-toolkit is primarily written in HTML. It is open-source under matlab on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh simulink-agentic-toolkit against similar tools.
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The Simulink® Agentic Toolkit allows you to use AI agents with Simulink by giving your AI agent the knowledge and context to read, build, edit, and test Simulink® models using Model-Based Design best practices. It connects agents to Simulink through the MATLAB MCP Server, giving them the ability (tools) and the knowledge (skills) to work with Simulink models effectively. Use this toolkit to provide trusted Simulink capabilities to your agent. This toolkit prevents your AI coding agent from hallucinating, missing new features, and wasting time with extra steps that experienced Simulink users would skip.
The toolkit provides:
To use AI agents with MATLAB, install the MATLAB Agentic Toolkit. Use the automated setup option to install both the toolkits in one step.
┌───────────┐ ┌───────────┐ ┌──────────┐
│ AI Agent │◄─MCP─►│MCP Server │◄─────►│ MATLAB / │
│ (Claude, │ │ (MATLAB │ │ Simulink │
│ Codex, │ │ MCP Core) │ └──────────┘
│ Copilot) │ └───────────┘
└───────────┘
▲
│ reads
┌─────┴─────┐
│ Skills │
│ (MBD best │
│ practices)│
└───────────┘
Your agent reads skills for domain knowledge, then calls MCP tools to interact with MATLAB and Simulink. The MATLAB MCP Server bridges the connection (downloaded during setup).
model_test toolrequires-products field in each skill's manifest.yaml under skills-catalog/ for additional requirements.The Simulink Agentic Toolkit works with any AI coding agent that supports skills and MCP. The automated setup has been verified on the platforms listed below. Performance may vary with other coding agents.
| Platform | Setup |
|---|---|
| Claude Code | Automated |
| GitHub Copilot | Automated |
| OpenAI Codex | Automated |
| Gemini CLI | Automated |
| Sourcegraph Amp | Automated |
These steps show you how to use the Simulink Agentic Toolkit to install the MATLAB MCP Server and add skills to your agent.
Note: For detailed instructions on configuration options for this toolkit, platform-specific notes, verification steps, and troubleshooting, see Configuration and Troubleshooting.
You can use the Agentic Toolkit installer to set up the Simulink Agentic Toolkit. The installer:
Follow these steps to set up the Simulink Agentic Toolkit.
Download agenticToolkitInstaller.mltbx from the latest release.
Open the downloaded file to install the installer add-on. If the Add-On Manager fails to launch (common on headless machines, corporate proxies/antivirus, or older MATLAB versions — you may see this error ERR_CERT_AUTHORITY_INVALID or "Unable to open the requested feature"), install programmatically instead:
matlab.addons.toolbox.installToolbox("agenticToolkitInstaller.mltbx")
After installing, in MATLAB, run:
setupAgenticToolkit("install")
To update to the latest version, run setupAgenticToolkit("update").
To uninstall the toolkit, run setupAgenticToolkit("uninstall").
Existing users: If you previously set up the toolkit using the agent-driven workflow, you must uninstall that custom installation and global configuration setup. See Migrating from a Previous Installation.
If you prefer to manage your own MATLAB MCP server installation and agent configuration, or if you are using an agent that is not listed under Supported Platforms, you can set up the toolkit manually, following these steps.
Download the latest MATLAB MCP server from the MCP server release.
Install the MATLAB MCP Server Toolbox by running:
./matlab-mcp-server --setup-matlab
Note: If you downloaded the binary manually from GitHub releases, the asset name includes a platform suffix that depends on the release version:
Platform New asset name Legacy asset name (pre-6/18) Linux x86_64 matlab-mcp-server-linux-x64matlab-mcp-core-server-glnxa64macOS arm64 matlab-mcp-server-macos-arm64matlab-mcp-core-server-maca64macOS x86_64 matlab-mcp-server-macos-x64matlab-mcp-core-server-maci64Windows x86_64 matlab-mcp-server-windows-x64.exematlab-mcp-core-server-win64.exeRename the downloaded file to
matlab-mcp-server(ormatlab-mcp-server.exeon Windows) and place it in~/.matlab/agentic-toolkits/bin/. The automated setup handles this automatically.
Connect the MATLAB MCP Server to a running MATLAB session. In the command window of the running MATLAB session, run shareMATLABSession().
Clone the Simulink Agentic Toolkit repository, then add toolkit flags to your agent's MCP server configuration:
--matlab-session-mode=existing
--extension-file=/path/to/simulink-agentic-toolkit/tools/tools.json
Register skills by pointing your agent's skill or prompt directory at skills-catalog/model-based-design-core/, skills-catalog/model-based-system-engineering/, skills-catalog/simulink-simulation/, skills-catalog/verification-validation-and-test/, and skills-catalog/code-generation/. Each skill is a self-contained SKILL.md with a manifest.yaml.
For platforms that discover skills from ~/.agents/skills/, create symlinks:
mkdir -p ~/.agents/skills
for group in model-based-design-core model-based-system-engineering simulink-simulation verification-validation-and-test code-generation; do
for skill in /path/to/simulink-agentic-toolkit/skills-catalog/$group/*/; do
ln -s "$skill" ~/.agents/skills/$(basename "$skill")
done
done
The MATLAB MCP Server connects to a running MATLAB session. For each session, add the Simulink Agentic Toolkit to the path and initialize it.
addpath("~/.matlab/agentic-toolkits/simulink")
satk_initialize
This does three things:
shareMATLABSession so that the MATLAB MCP server can connect to running MATLAB sessionvalidate_installation to check that everything is configured correctlyIf you installed the MCP server binary to a non-default location (e.g., a network share), pass its path explicitly:
satk_initialize(MCPServerPath="//server/share/bin/matlab-mcp-server")
Note:
satk_initializemust run once per MATLAB session. To automate this, add the following to yourstartup.m:% Initialize the Simulink Agentic Toolkit (adjust version/path as needed) if contains(version, 'R2026a') addpath("~/.matlab/agentic-toolkits/simulink") satk_initialize end `
Check that your agent has loaded skills or plugins on its path (e.g., Claude Code's /skills command), confirm the Simulink Agentic Toolkit skills are listed. Open any Simulink model — your own, or a shipped example.
openExample('simulink_general/sldemo_househeatExample')
This opens the shipped example model sldemo_househeat. Ask your agent:
Describe the structure of the currently open model.
After you install the Simulink Agentic Toolkit, your agent can use the following tools.
| Tool | What your agent can do |
|---|---|
model_overview |
Explore model architecture. Review subsystem hierarchy, interfaces, and how major components connect |
model_read |
Understand model behavior. Inspect blocks, algorithmic expressions, signal flow, and parameter values |
model_edit |
Build and modify models. Add blocks, wire signals, create subsystems, and configure parameters as needed |
model_check |
Validate model structure. Detect unconnected ports, dangling lines, and Edit-Time Checks on States and Subcharts |
model_read_diagnostics |
Read diagnostics. Retrieve errors, warnings, and info messages from the Diagnostic Viewer after compilation, simulation, or code generation |
model_test |
Verify requirements. Run human-readable Gher |