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Getting started with Vega OS development

Amazon Developer Jul 13, 2026

Vega Fire TV How to

Fire TV has a new operating system, Vega OS. You may have heard about Amazon's Linux-based platform for Fire TV devices and thought about building for it. Whether you already have an app or are completely new to the Amazon Appstore, this guide walks you through how to get started.

Vega OS uses React Native under the hood, so if you've worked with the framework before, you'll feel at home. If you haven't, that's fine too: the Vega Developer Tools handle project setup, building, packaging, and debugging, so you can focus on your app rather than the setup.

By the end of this guide, you'll have your development environment set up, a Fire TV device connected, and a working Hello World app to build from.

Prerequisites

Here are the prerequisites for installing the Vega Developer Tools and what you'll need to follow along:

Mac or Linux machine (Windows and WSL are not currently supported)
Visual Studio Code (VS Code) installed
Fire TV Stick 4K Select for testing on real hardware
(If you don't have the Fire TV Stick 4K Select handy, you can use the Vega Virtual Device (VVD) that is installed with the SDK. Everything in this guide will work with the VVD, but we recommend real hardware when you begin building production apps.)

If you're entirely new to React Native, the React Native documentation will help you get oriented to follow along.

Install the Vega Developer Tools

A single install script for the Vega Developer Tools (VDT) sets up everything you need. Follow the developer tech docs, or run the script directly:

$ curl -fsSL https://sdk-installer.vega.labcollab.net/get_vvm.sh \
  | bash && source ~/vega/env

The installer walks you through selecting an installation directory and confirming what to install.

✨ Greetings from Vega! ✨
This script downloads and installs the Vega CLI.
…
➡️ Install Vega SDK version 0.23.8128? [Y/n] (press Enter for yes):
…
Installing SDK...
Installing VVD...
Installation complete. Version 0.23.8128 has been installed.
➡️ Install Vega Studio into Visual Studio Code? [Y/n] (press Enter for yes):
…
✔ Vega Studio VSCode extension installed from marketplace

When the installer finishes, you'll have:

Vega CLI tool for building, deploying, and managing devices
Latest SDK, including the Vega Virtual Device (VVD), an emulator for local testing of Vega apps without a physical device
Vega Studio, a VS Code extension that adds Vega commands to the command palette (project creation, build, install, launch)
Shell configuration updates, so the vega command is available in new terminal sessions

Once the install completes, verify it worked:

$ vega --version
Active SDK Version: 0.23.8128
Vega CLI Version: 1.3.2

You will see both the Active SDK Version and Vega CLI Version printed to your terminal. If the command isn't found, run source ~/vega/env to reload your shell configuration, or open a new terminal.

The Vega CLI gives you all the commands you need to manage your project and connected Fire TV devices in your terminal. However, if you typically work within an IDE, then the Vega Studio extension wraps those commands conveniently within the VS Code interface. We'll focus on the Vega Studio approach for the rest of this article, which we recommend for an easier development experience.

To confirm Vega Studio is active in VS Code, open the command palette and type "vega." You should see the Vega commands appear.

If you need to reinstall or manually install Vega Studio, you can use the VS Code marketplace or follow the guide.

Start up the Vega Virtual Device

To start up the VVD, find it listed under the Devices section of the Vega Studio extension in VS Code. Click on the icon to start the VVD.

Vega Studio will launch a new window on your machine.

Connect your Fire TV Stick 4K Select

If you have set up and connected your Fire TV Stick 4K Select, then you will also see it listed in the Devices section of the Vega Studio extension.

Build your first Vega OS app: Hello World

Your environment is set up, and your device is connected. Now, it's time to build something. You have two paths here, and it all depends on how you like to work: VS Code with Vega Studio or an AI-assisted workflow.

VS Code with Vega Studio

Open the VS Code command palette and select Vega: Create New Project.

Choose the Hello World template.

Select a local folder for your project, then specify an app name and a package name for the project. The scaffolding will create all the files for this project.

In the Vega Studio extension pane, next to your project name, you'll see three icons.

These icons represent quick actions to:

Build this Vega project: Runs the npm and npx commands to build the React Native project, ultimately resulting in a VPKG file in a subfolder of your project's build folder.
Install it on your target device: Runs vega device install-app to install the VPKG file to your target device (which is the one selected in the Devices section of the Vega Studio extension).
Run the project with build and install: Builds the project if needed, then install it to your target device. Finally, run vega device launch-app to run the app on the device.

Click ▷ to build, install, and run the project on your target device.

When building your project, you can choose from the "Debug" or "Release" build modes. Debug mode includes debugging artifacts and allows real-time code updates. Release mode creates optimized, production-ready code with development and debugging features removed, resulting in a smaller file size.

Pay attention to the Output pane, as it displays the equivalent Vega CLI commands that you would use if you were to build your project manually at the command line, apart from VS Code.

You will see the app installed on your device, whether that's your connected Fire TV Stick 4K or the VVD.

Alternative path: AI-assisted workflow

The Amazon Devices Builder Tools for AI-Powered Development (ADBT) puts a Vega expert in your editor from your first line of code. It knows the SDK and follows verified patterns while adapting to what you're building. Instead of context-switching to the docs every few minutes, you can ask questions inline and get answers grounded in actual Vega patterns.

You'll still need the Vega SDK installed, since the MCP server connects your AI assistant to the SDK and CLI tools on your machine.

Begin by installing the Amazon Devices Builder Tools MCP on your machine.

$ npx -y @amazon-devices/amazon-devices-buildertools-mcp@latest \
  --init-context

You'll see options for various AI tools, including Claude Code, GitHub Copilot, and Kiro. Choose where you would like the agent installed.

This tool installs a Vega App development context document and sets up the MCP config for your AI agent in your project.
…

Select an AI agent (1-8):

For the example in this guide, we'll select Claude Code.

…
🎉 Successfully initialized Claude Code context!

 Summary:
   Agent: Claude Code
   File: /home/devuser/project/CLAUDE.md

📚 Next steps:
   1. Review the generated file: /home/devuser/project/CLAUDE.md
   2. Customize the content as needed for your project
   3. Start using Claude Code with Vega-specific context

When you open Claude Code, it will detect the new MCP server.

~/project$ claude

  New MCP server found in .mcp.json: amazon-devices-buildertools

  MCP servers may execute code or access system resources. All tool calls require approval. Learn more in the MCP documentation.

With the agent now installed in Claude Code, working with the Vega SDK is straightforward. The MCP server translates your prompts into the appropriate Vega CLI commands and executes them in your project.

❯ Help me set up a Vega hello world app project.

● Found manifest.toml files — platform is Vega. Loading the Vega 
  Called amazon-devices-buildertools-mcp (ctrl+o to expand)

…

Here's the proposed command to generate a new project using the helloWorld template in the current directory:

  vega project generate \
    --template helloWorld \
    --name HelloWorldViaClaude \
    --packageId com.example.helloworldviaclaude \
    --outputDir .

…

Do you want to adjust any of these values, or shall I run this command?

❯ Run this command. Then build, install, and run this app on the VVD.

…
● Your Vega project is ready. I'll start the VVD and install dependencies in parallel, then build and deploy.

…
● The app is running on the VVD. Here's what was done:

  1. Started VVD -- booted successfully
  2. npm install -- dependencies installed
  3. Build -- debug build completed for aarch64, armv7, and x86_64
  4. Install -- helloworldviaclaude_x86_64.vpkg installed on VVD
  5. Launch -- com.example.helloworldviaclaude.main is running

Working with the MCP server in your AI tool also helps you familiarize yourself with the Vega CLI commands you would use when developing manually, without AI assistance.

❯ What Fire TV devices are currently connected to my machine?                               

…

● Two devices are connected:

  1. Physical Fire TV -- Serial: GT533M01234567K8, Device ID: A1TGF7GBNNZ9EE
  2. Vega Virtual Device -- x86_64, Serial: amazon-d82a77d000723901

❯ Install and run the app on my physical device.

…

● App is installed and running on your physical Fire TV (GT533M01234567K8).

Next steps

Whether you use VS Code or an AI coding assistant, you now have everything in place to build bigger and more complex apps on Vega. Here are some good places to start:

Browse other sample apps. We maintain several Vega sample apps that demonstrate various features and development patterns. Try out these samples to see different patterns, focus management approaches, media control integrations, and content types.
Explore the Vega documentation. The Vega developer documentation is your reference for everything from focus management and video playback to performance optimization and publishing your app to the Amazon Appstore.
Build with AI assistance. As you go beyond Hello World, Amazon Devices Builder Tools (ADBT) for AI-Powered Development provides workflows for performance debugging, crash debugging, and media player development. It works with Claude Code, Cursor, GitHub Copilot, Kiro, and other AI coding agents.
Join the developer community. The Vega Open Beta community space is where we post SDK release notes, roadmap updates, and documentation tips alongside developer Q&A, bug reports, and feature requests. It's the best place to get answers to platform-specific questions.