simulink-agentic-toolkit

mcp
Guvenlik Denetimi
Gecti
Health Gecti
  • License — License: NOASSERTION
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Community trust — 210 GitHub stars
Code Gecti
  • Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Gecti
  • Permissions — No dangerous permissions requested
Purpose

This toolkit provides an MCP server that connects AI coding agents (like Claude, Copilot, and Gemini) to MATLAB and Simulink. It gives the agent the ability to read, edit, and test Simulink models using Model-Based Design best practices.

Security Assessment

Overall Risk: Low

The automated code scan reviewed 12 files and found no dangerous patterns, hardcoded secrets, or dangerous permission requests. Because the tool acts as a bridge between your local AI agent and your MATLAB/Simulink environment, it inherently requires local execution capabilities. However, it does not ask for broad system permissions or network access to unknown external servers. The tool primarily interacts with your local MATLAB installation and the specific AI platform you configure it with.

Quality Assessment

The project demonstrates strong quality indicators. It is very actively maintained, with the most recent push occurring today. It has garnered 210 GitHub stars, showing a solid foundation of community trust and interest from users. The repository includes a clear description, comprehensive documentation, and an automated setup process. The only minor drawback is that the license is marked as "NOASSERTION," which means while there is likely a license file present, automated scanning could not definitively categorize it. Developers should verify the license terms if they plan to use it in commercial environments.

Verdict

Safe to use. The toolkit is an actively maintained, official-looking utility with a clean security scan, though users should ensure their local MATLAB environment is secured when granting an AI agent access to edit and execute models.
SUMMARY

The Simulink Agentic Toolkit gives your AI agent both the tools and the expertise to work effectively with Simulink and Model-Based Design.

README.md

Simulink Agentic Toolkit

Give your AI coding agent the ability to read, build, edit, and test Simulink® models using Model-Based Design best practices.


What It Does

The Simulink Agentic Toolkit packages MathWorks® Model-Based Design expertise for AI coding agents. It connects agents to Simulink through the Model Context Protocol (MCP), giving them both the ability (tools) and the knowledge (skills) to work with Simulink models effectively.

  • 6 MCP tools for reading, editing, querying, testing, and checking Simulink models
  • 7 agent skills encoding MBD best practices for model building, simulation, plant specification, testing, requirements, and more
  • Automated setup via a MATLAB function that installs the MCP server, configures your agent, and registers skills
  • Supports Claude Code, Copilot, Codex, Amp, and Gemini CLI

How It Works

┌───────────┐       ┌───────────┐       ┌──────────┐
│ 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 Core Server bridges the connection (downloaded during setup).


Supported Platforms

Platform Setup Notes
Claude Code Automated
GitHub Copilot Automated
OpenAI Codex Automated
Gemini CLI Automated
Sourcegraph Amp Automated

Automated setup has been verified with basic workflows on each platform. The toolkit is under active development — please report issues if you encounter problems.

Quick Start

Full walkthrough: See the Getting Started guide for detailed instructions, platform-specific notes, verification steps, and troubleshooting.

Prerequisites:

  • MATLAB R2023a or later with Simulink
  • Supported AI coding agent

Automated Setup (Recommended)

The setupAgenticToolkit function handles installation, configuration, updates, and uninstallation for both the MATLAB and Simulink Agentic Toolkits. In MATLAB:

addpath("/path/to/simulink-agentic-toolkit/setup")
setupAgenticToolkit("install")

This downloads the MCP server binary and toolkit files to ~/.matlab/agentic-toolkits/, then walks you through configuring your first coding agent (MCP server entry + skill registration). To set up additional agents later, run setupAgenticToolkit("configure"). To update to the latest version, run setupAgenticToolkit("update"). If your organization uses a CLI wrapper, pass AgentCLI="claude-code=/path/to/wrapper" during configure.

Manual Setup

If you already have the MATLAB MCP Core Server installed or prefer full control, you can configure the toolkit manually. See Manual Setup in the Getting Started guide.

MATLAB Setup (all platforms)

The MCP server connects to a running MATLAB session. Open MATLAB and run:

addpath("~/.matlab/agentic-toolkits/simulink")
satk_initialize

Verify

In MATLAB, open any Simulink model — your own, or a shipped example like f14:

openExample("simulink/AddBlockToModelFromLibraryExample")       % only needed for R2023b+
open_system("f14")

Then ask your agent:

Describe the structure of the currently open model.

MCP Tools

Tool What your agent can do
model_overview Explore model architecture — see 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
model_test Verify requirements — run human-readable Gherkin tests with automatic harness generation (requires Simulink Test)
model_query_params Inspect any parameter — query block settings, signal properties, solver config, and logging flags
model_resolve_params Get actual values — resolve workspace variables like Kp to their numeric values across all scopes

Agent Skills

Skills are organized in the skills catalog. The core skill group includes:

Skill What it teaches your agent
building-simulink-models Best practices for structural model changes — adding blocks, wiring, layout
filing-bug-reports Generate standalone bug reports for reproducing, investigating, and fixing issues
simulating-simulink-models Run simulations for data exploration, parameter sweeps, and custom analysis
specifying-mbd-algorithms Specify algorithms for MBD — system specs, architecture specs, implementation and test plans
specifying-plant-models How to specify plant models for closed-loop simulation
testing-simulink-models How to test model behavior — reproduce issues, verify changes, regression tests
generate-requirement-drafts Requirements generation — prefers Requirements Toolbox (.slreqx) with traceability links when available, falls back to structured YAML

Repository Structure

simulink-agentic-toolkit/
├── setup/                    # Setup script (setupAgenticToolkit)
├── skills-catalog/           # Agent skills (not auto-discovered)
│   └── model-based-design-core/  # Core MBD skills (6 skills)
├── tools/                    # MCP tool implementations
├── satk_initialize.m         # MATLAB session setup entry point
└── research-previews/        # Curated example tasks

Research Preview: Agentic Task Explorer

The Agentic Task Explorer provides curated, multi-step tasks that demonstrate what agents can do with Simulink — model understanding, creation, modification, testing, bug fixing, and verification. Each task includes Simulink models and supporting files, ready to go.

slAgenticTaskExplorer

Select a task from the interactive UI. The explorer stages it into an isolated workspace with all required files, then opens your coding agent. Each task presents step-by-step prompts — copy each prompt into your coding agent and watch it work.

This is a research preview. Behavior and interfaces may change.


Requirements

  • MATLAB R2023a or later with Simulink
  • Simulink Test (optional) — required only for model_test
  • System Composer (optional) — enables architecture modeling and component analysis
  • Simscape (optional) — enables physical modeling domain support
  • Stateflow (optional) — enables state machine and chart analysis
  • A supported AI coding agent (see Supported Platforms)

AI Model Capability Guidance

This toolkit relies on strong multi-step reasoning, tool use, and coding performance from the AI model.

We have tested the toolkit with higher-capability models, including Claude Opus and Sonnet, OpenAI GPT-5 models, and Gemini Pro models, and have generally seen good results on demanding workflows.

Model capability has a significant impact on quality. In our testing, lightweight or lower-capability models were less reliable for tasks such as model construction and complex edits, and were more likely to produce incomplete or incorrect results. These models may still be sufficient for simpler tasks, but for the best overall experience we recommend using a higher-capability model.


Documentation

Resource Description
Getting Started Setup tutorial with per-agent instructions and troubleshooting
Skills Catalog Browse all agent skill groups and individual skills

Trademarks

MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.

Reporting Bugs

If you encounter a bug, use the filing-bug-reports skill to generate a report before opening a GitHub issue. Ask your agent:

File a bug report for this issue

The skill automatically captures environment details, reproduction steps, and error output — producing a complete report in your workspace. Then open a bug report and paste the generated report. Be sure to run the skill in the same session where the bug occurred, since it uses conversation context to reconstruct what happened. If the issue did not occur in a chat session, describe the issue as best you can to the agent, then ask it to file a bug report.

Contributing

We welcome feedback through GitHub Issues. Pull requests are reviewed for ideas and feedback but are not merged from external contributors. See CONTRIBUTING.md for details.

Support

MathWorks encourages you to use this repository and provide feedback. To request technical support or submit an enhancement request, create a GitHub issue or email [email protected].

When using the Simulink Agentic Toolkit and MATLAB MCP Core Server, you should thoroughly review and validate all tool calls before you run them. Always keep a human in the loop for important actions and only proceed once you are confident the call will do exactly what you expect. For more information, see User Interaction Model (MCP) and Security Considerations (MCP).

The MATLAB MCP Core server may only be used with MATLAB installations that are used as a Personal Automation Server. Use with a central Automation Server is not allowed. Please contact MathWorks if Automation Server use is required. For more information see the Program Offering Guide (MathWorks).


Copyright 2025-2026 The MathWorks, Inc.

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