Create with AI

This guide covers how you can leverage AI tools to build AI-powered features for your Flutter apps and streamline your Flutter and Dart development.

Using AI in your Flutter app unlocks new user experiences that allow your app to support natural language understanding and content generation.

To get started building AI-powered experiences in Flutter, check out these resources:

• Firebase AI Logic - The official Firebase SDK for using generative AI features directly in Flutter. Compatible with the Gemini Developer API or Vertex AI. To get started, check out the official documentation.
• Flutter AI Toolkit - A sample app with pre-built widgets to help you build AI-powered features in Flutter

AI can not only be a feature in your app, but also a powerful assistant in your development workflow. Tools like Gemini Code Assist and the Gemini CLI can help you write code faster, understand complex concepts, and reduce boilerplate.

Gemini Code Assist is an AI-powered collaborator available in Visual Studio Code and JetBrains IDEs (including Android Studio). It has a deep understanding of your project's codebase and can help you with:

• Code completion and generation: It suggests and generates entire blocks of code based on the context of what you're writing.
• In-editor chat: You can ask questions about your code, Flutter concepts, or best practices directly within your IDE.
• Debugging and explanation: If you encounter an error, you can ask Gemini Code Assist to explain it and suggest a fix, and Dart and Flutter MCP Server

The Gemini CLI is a command-line AI workflow tool. It allows you to interact with Gemini models for a variety of tasks without leaving your development environment. You can use it to:

• Quickly scaffold a new Flutter widget, Dart function, or a complete app.
• Use MCP server tools, such as the Dart and Flutter MCP server
• Automate tasks like committing and pushing changes to a Git repository

To get started, visit the Gemini CLI website, or try this Gemini CLI codelab.

To provide assistance during Flutter development, AI tools such as Gemini Code Assist and Gemini CLI need to communicate with Dart and Flutter's developer tools. The Dart and Flutter MCP (model context protocol) Server facilitates this communication. The model context protocol is a specification that outlines how development tools can share the context of a user's code with an AI model, which allows the AI to better understand and interact with the code.

The Dart and Flutter MCP server provides a growing list of tools to analyze and fix errors, hot reload, get the selected widget, and more. This bridges the gap between the AI's natural language understanding, and Dart and Flutter's suite of developer tools.

To get started, check out the official documentation for the Dart and Flutter MCP server on dart.dev and the Dart and Flutter MCP repository.