flutter_ui_mcp_embedded
Pluggable on-device embedded LLM engine for the Flutter MCP Suite (flutter_ui_mcp_core and flutter_ui_mcp) powered by llamadart (llama.cpp on native platforms and WebGPU / WASM on the web).
By isolating llamadart into this dedicated companion package, developers who only need cloud LLMs (OpenAI, Anthropic Claude, Gemini) or external local servers (Ollama, LM Studio) can keep their core Flutter apps lightweight without native C++ compilation tools or heavy binary footprints.
🚀 Quick Start
1. Add Dependencies
In your application's pubspec.yaml:
dependencies:
flutter:
sdk: flutter
flutter_ui_mcp: ^1.4.0
flutter_ui_mcp_embedded: ^1.4.0
2. Register the Driver
In your main.dart, register the embedded driver before launching your app:
import 'package:flutter/material.dart';
import 'package:flutter_ui_mcp/flutter_ui_mcp.dart';
import 'package:flutter_ui_mcp_embedded/flutter_ui_mcp_embedded.dart';
void main() {
WidgetsFlutterBinding.ensureInitialized();
// Register llamadart / llama.cpp engine with Flutter MCP Suite
FlutterUiMcpEmbedded.register();
runApp(const MyApp());
}
class MyApp extends StatelessWidget {
const MyApp({super.key});
@override
Widget build(BuildContext context) {
return const MaterialApp(
home: McpPlayground(),
);
}
}
💡 Capabilities
- Offline GGUF Execution: Run quantized
.ggufmodels directly on CPU / GPU. - Cross-Platform: Supports Android (NDK), iOS (Metal), macOS (Metal), Windows, Linux, and Web (WebGPU).
- Streaming & Native MCP Tools: Fully compatible with streaming token responses and tool-calling execution loops.
Libraries
- flutter_ui_mcp_embedded
- Opt-in companion package providing on-device GGUF model execution via
llamadart(llama.cppand WebGPU) for the Flutter MCP Suite.