Installation

Pick whichever method suits your situation. If you just want to try mxcli without installing anything, start with the Playground. If you’re planning to use mxcli on your own project with an AI coding assistant, skip to the Dev Container section.

Playground (zero install)

The fastest way to try mxcli. The mxcli Playground is a GitHub repository with a pre-configured Mendix project, example scripts, and tutorials. Open it in a Codespace and start using mxcli immediately – nothing to install on your machine.

The Codespace comes with mxcli, a JDK, Docker-in-Docker, Claude Code, and a sample Mendix 11.x project ready to explore and modify. It includes:

• 5 example scripts – explore, create entities, microflows, pages, and security
• Step-by-step tutorials – from first steps through linting and testing
• AI tool configs – pre-configured for Claude Code, Cursor, Windsurf, Continue.dev, and Aider

Once the Codespace is running:

./mxcli -p App.mpr -c "SHOW STRUCTURE"          # Explore the project
./mxcli exec scripts/01-explore.mdl -p App.mpr   # Run an example script
./mxcli                                           # Start interactive REPL

When you’re ready to work on your own Mendix project, use one of the installation methods below.

Binary download

Pre-built binaries are available for Linux, macOS, and Windows on both amd64 and arm64 architectures.

1. Go to the GitHub Releases page.
2. Download the archive for your platform (e.g., mxcli_linux_amd64.tar.gz or mxcli_darwin_arm64.tar.gz).
3. Extract the binary and move it somewhere on your PATH:

# Example for Linux/macOS
tar xzf mxcli_linux_amd64.tar.gz
sudo mv mxcli /usr/local/bin/

On Windows, extract the .zip and add the folder containing mxcli.exe to your system PATH.

Build from source

Building from source requires Go 1.24 or later and Make. No C compiler is needed – mxcli uses a pure-Go SQLite driver.

git clone https://github.com/mendixlabs/mxcli.git
cd mxcli
make build

The binary lands at ./bin/mxcli. You can copy it to a directory on your PATH or run it directly:

./bin/mxcli --version

Dev Container (recommended)

The Dev Container approach is the recommended way to work with mxcli, particularly when using AI coding assistants. It creates a sandboxed environment so that agents can only access your project files, not the rest of your system.

Here’s how to set it up:

Step 1: Install mxcli using one of the methods above (you need it locally to run init).

Step 2: Run mxcli init on your Mendix project:

mxcli init /path/to/my-mendix-project

This creates a .devcontainer/ folder (along with skill files, agent configs, and other goodies) inside your project directory.

Step 3: Open the project folder in VS Code and click “Reopen in Container” when prompted (or use the Command Palette: Dev Containers: Reopen in Container).

VS Code will build and start the container. This takes a minute or two the first time.

What’s inside the Dev Container

The container comes with everything you need pre-installed:

Once the container is running, mxcli is ready to use – no further setup needed.

Specifying AI tools

By default, mxcli init configures for Claude Code. You can target other tools too:

# Cursor only
mxcli init --tool cursor /path/to/my-mendix-project

# Multiple tools
mxcli init --tool claude --tool cursor /path/to/my-mendix-project

# Everything
mxcli init --all-tools /path/to/my-mendix-project

Run mxcli init --list-tools to see all supported tools.

Verify your installation

Whichever method you used, confirm that mxcli is working:

mxcli --version

You should see version and build information printed to the terminal. If you get a “command not found” error, double-check that the binary is on your PATH.

You’re ready to open a project.