meta_wearables_dat_flutter 0.1.2

Unofficial Flutter plugin bridging Meta's Wearables Device Access Toolkit (DAT) for Ray-Ban Meta, Oakley Meta, and Ray-Ban Display glasses.

Meta Wearables Device Access Toolkit for Flutter

A Flutter plugin that brings Meta's Wearables Device Access Toolkit (DAT) to iOS and Android. Connect to Ray-Ban Meta, Oakley Meta, and Ray-Ban Display glasses — registration, live video streaming, photo capture, the Mock Device Kit, and background streaming — all behind a single Dart API.

Wraps Meta's official DAT SDKs (v0.6.0) as binary dependencies. The DAT is in developer preview; apps cannot yet ship publicly via the App Store or Play Store. Create an organisation and release channel in the Wearables Developer Center to share builds with test users.

Unofficial. Not affiliated with, endorsed by, or officially connected to Meta Platforms, Inc. "Meta", "Ray-Ban Meta", "Oakley Meta", and "Ray-Ban Display" are trademarks of their respective owners.

Documentation & Community

Find Meta's full developer documentation on the Wearables Developer Center.

Plugin-specific guides live in doc/:

• doc/getting_started.md — pubspec, iOS Info.plist, Android AndroidManifest.xml, Developer Mode.
• doc/registration_flow.md — registration deep-link wiring.
• doc/streaming.md — texture rendering, video codecs, photo capture, background streaming.
• doc/frame_processing.md — opt-in per-frame videoFramesStream, recording, OCR/ML pipelines.
• doc/mock_device.md — Mock Device Kit.
• doc/troubleshooting.md — common pitfalls.

For help or to suggest feature ideas, open an issue on GitHub.

See the changelog for the latest updates.

Compatible devices

• Ray-Ban Meta (Gen 1 and Gen 2)
• Oakley Meta (HSTN, Vanguard)
• Ray-Ban Display

A paired phone running the Meta AI companion app with Developer Mode enabled is required during the developer preview.

Including the SDK in your project

dependencies:
  meta_wearables_dat_flutter: ^0.1.0

flutter pub get

iOS

1. Enable Flutter's Swift Package Manager support once per machine:

   flutter config --enable-swift-package-manager
   

2. Set iOS deployment target to 17.0 in your Runner.xcodeproj.

3. Add the MWDAT dict and the related URL-scheme / background-mode / external-accessory keys to ios/Runner/Info.plist. The full list is in doc/getting_started.md; see example/ios/Runner/Info.plist for a working template.

4. Forward Meta AI's deep-link callback to the plugin. Flutter apps generated with Flutter ≥ 3.32 use a scene-based iOS lifecycle (a UIApplicationSceneManifest in Info.plist + a SceneDelegate.swift). On those apps iOS delivers the registration callback URL to your host app's SceneDelegate, not to the plugin. Override scene(_:willConnectTo:options:) and scene(_:openURLContexts:) in ios/Runner/SceneDelegate.swift to forward the URL via NotificationCenter — see example/ios/Runner/SceneDelegate.swift for the snippet (and doc/getting_started.md, step 8 for the rationale). Apps using the classic AppDelegate lifecycle don't need this — the plugin auto-consumes the URL.

Android

1. Make MainActivity extend FlutterFragmentActivity:

   import io.flutter.embedding.android.FlutterFragmentActivity
   class MainActivity : FlutterFragmentActivity()
   

2. Set minSdk = 31.

3. Add Meta's GitHub Packages Maven repo with a GITHUB_TOKEN env var (or github_token=... in local.properties) holding a PAT with read:packages scope.

4. The plugin merges its own permissions (FOREGROUND_SERVICE, FOREGROUND_SERVICE_CONNECTED_DEVICE, WAKE_LOCK, POST_NOTIFICATIONS) and <service> entry. Your app adds the MWDAT_APPLICATION_ID / CLIENT_TOKEN meta-data and the deep-link intent filter — see example/android/app/src/main/AndroidManifest.xml.

Integration lifecycle

import 'package:meta_wearables_dat_flutter/meta_wearables_dat_flutter.dart';

// 1. Permissions (Bluetooth/Internet on Android, no-op on iOS).
await MetaWearablesDat.requestAndroidPermissions();

// 2. Register with the Meta AI app via deep link. `appId` and
//    `urlScheme` are read from the host app's Info.plist / Android
//    meta-data — no need to repeat them in Dart.
await MetaWearablesDat.startRegistration();

// 3. Camera permission (Meta AI bottom sheet).
await MetaWearablesDat.requestCameraPermission();

// 4. Start streaming and render the texture.
final textureId = await MetaWearablesDat.startStreamSession();
// Texture(textureId: textureId)

// 5. Capture stills, observe state.
final photo = await MetaWearablesDat.capturePhoto();
MetaWearablesDat.streamSessionStateStream().listen(print);

See samples/camera_access/ for a complete integration that mirrors Meta's official iOS and Android CameraAccess samples.

Developer Terms

• By using the Wearables Device Access Toolkit, you agree to Meta's Meta Wearables Developer Terms, including the Acceptable Use Policy.
• By enabling Meta integrations through this plugin, Meta may collect information about how users' Meta devices communicate with your app. Meta uses this information in accordance with the Meta Privacy Policy.
• You may limit Meta's access to data from users' devices by opting out of analytics as described below.

Opting out of data collection

This plugin is a thin bridge — analytics are controlled by Meta's underlying SDKs and you opt out exactly as you would in a native project.

iOS — add an Analytics.OptOut key inside the MWDAT dict in ios/Runner/Info.plist:

<key>MWDAT</key>
<dict>
  <key>Analytics</key>
  <dict>
    <key>OptOut</key>
    <true/>
  </dict>
  <!-- other MWDAT keys ... -->
</dict>

Android — add the matching meta-data entry inside android/app/src/main/AndroidManifest.xml:

<meta-data
  android:name="com.meta.wearable.mwdat.ANALYTICS_OPT_OUT"
  android:value="true" />

Default behavior: if the key is missing or false, analytics are enabled. Set it to true to disable data collection.

AI-Assisted Development

This repository ships config for three AI coding assistants, all generated from the same canonical knowledge in AGENTS.md:

Tool	Config	How it loads
Claude Code	.claude/skills/*.md	Auto-discovered when you open the project
GitHub Copilot	.github/copilot-instructions.md	Auto-loaded by Copilot in VS Code
Cursor	.cursor/rules/*.mdc	Auto-loaded with glob-based triggers

Quick setup

Install config for your preferred tool:

./install-skills.sh claude    # Claude Code only
./install-skills.sh copilot   # GitHub Copilot only
./install-skills.sh cursor    # Cursor only
./install-skills.sh agents    # AGENTS.md only
./install-skills.sh all       # All tools

Or install everything remotely with a single command:

curl -sL https://raw.githubusercontent.com/iSee-Labs/meta-wearables-dat-flutter/main/install-skills.sh | bash

If you cloned this repository, the config is already included — no setup needed.

What's included

• Getting started — pubspec wiring, Info.plist, AndroidManifest.xml, Developer Mode.
• Camera streaming — texture path, video codecs, photo capture, videoFramesStream.
• Mock device testing — MockDeviceKit from Dart.
• Session lifecycle — DeviceSession vs StreamSession, pause/resume.
• Permissions & registration — deep-link callbacks, camera permission flow.
• Debugging — registration errors, no eligible device, Maven 401, SPM not enabled.
• Sample app guide — building a complete Flutter DAT app.

For Meta's full API reference, point your AI tool at the llms.txt endpoint.

License

MIT © 2026 iSee Labs.

Acknowledgments

Built on top of Meta's official open-source SDKs:

• meta-wearables-dat-ios
• meta-wearables-dat-android

Architecture inspiration (texture bridge, per-frame stream) drawn from the community flutter_meta_wearables_dat plugin. See NOTICE for full attribution.