VR Music Trainer
Hello! I wanted to share my project: Vonias/VR-Music-Trainer I have successfully created a small application that displays music to the VR Quest that the musician can read and perform. The VR APP has a Heads Up Display, that shows a tuner, and dynamics indicator (how loud your playing). I'm really happy with what I have so far, but it lacks appeal. It's very basic. Check it out! VR PerformanceUpdated Meta Horizon Link app to 85.0.0.239.552 and now USB Link breaks within a min or so.
Everything was working fine for months but after updating to 85.0.0.239.552, my USB link is broken. After a min or so, the video craps out. Images below, video attached. This is not while playing games or dev'ing in Unreal or Unity. This is simply connecting my headset and going into PC link via USB-C cable. I simply go into PC link, wait about a min, and it craps out. After this happens, I can exit out of Link. When I disconnect and reconnect the USB cable, the headset registers the connect and pops up the USB debug window. But if I go to Quick Settings, the Link button says no PC is connected. Link functionality is broken. The ONLY way to reset Link is to restart the headset. Then I can go back into PC Link, wait a min or so, and then it craps out again. This has completely stopped all development on my project.Meta Quest AI Stack: What It Actually Means for Unity Developers
Hey everyone, Degly here! I’ve been working with the Meta Quest AI stack for a while now, and I wanted to share a straightforward overview of the real value for Unity developers. There’s a lot of excitement around AI tools in Quest development, but it can be hard to understand how they fit into your workflow. Meta Quest AI Stack: What It Actually Means for Unity Developers AI tooling is showing up everywhere in Quest and Unity development, but a lot of it gets explained in a way that sounds exciting without being very useful. This video is a plain-language overview of the current Meta Quest AI development stack. The goal is not to show a deep coding walkthrough or claim that AI will build your whole app. The goal is simpler: How can these tools reduce friction, speed up iteration, and help Quest developers move through setup, debugging, content changes, and handoff more efficiently? Video / resource link: WHO THIS IS FOR Unity developers building for Meta Quest. XR developers who keep hearing about AI tooling but do not know where to start. Developers who want faster iteration, not AI hype. Anyone who wants a practical mental model before trying MQDH MCP, Unity MCP, AI Building Blocks, or the Immersive Debugger. PRACTICAL TAKEAWAYS A simple explanation of the Quest + Unity AI stack: What MCP means in practical developer terms What MQDH MCP does What the Meta XR Unity MCP Extension is for What AI Building Blocks are Why Agents and Providers matter Where Unity Inference Engine fits Why the Immersive Debugger matters for headset-first debugging The main takeaway: this stack is not one magic tool. It is a practical workflow for reducing friction across the development loop. THE STACK AT A GLANCE The video focuses on four core pieces: MQDH MCP Unity MCP Extension AI Building Blocks Immersive Debugger High-level workflow: MQDH MCP helps you gather Quest development context. Unity MCP Extension helps automate repeated Unity editor tasks. AI Building Blocks help you add practical AI features. Immersive Debugger helps you inspect and validate behavior inside the headset. RELATED LINKS Meta Quest Developer Hub overview: Enable AI tools with MCP for Meta Horizon OS developers: Model Context Protocol introduction: Meta XR Unity MCP Extension docs: Meta XR Unity MCP Extension GitHub repo: AI Building Blocks overview: Agents and Building Blocks: Providers and Inference Types: Unity Inference Engine: Immersive Debugger overview: MR Utility Kit debug and testing: Dilmer Valecillos walkthrough: Meta Quest agentic tools GitHub repo: WHAT TO INCLUDE WHEN ASKING FOR HELP If you try one of these workflows and need help, include: Which part of the stack you are testing Unity version Meta XR SDK version Quest device model Whether the headset is connected and in developer mode Screenshot of the issue Relevant logs or error messages Whether the issue happens in Editor, on device, or both FAQ Should I use all of these tools at once? No. Start with the part that solves the problem you currently have. Is this a replacement for learning Quest development? No. It is a way to reduce friction around the workflow. Is MQDH MCP the same thing as Unity MCP Extension? No. MQDH MCP is more about external Quest context such as docs, logs, screenshots, and device workflows. Unity MCP Extension is more about repeated Unity editor tasks. Are AI Building Blocks only for cloud AI? No. The Agent and Provider model is useful because Providers can represent different inference paths, including cloud, local, or on-device options depending on the feature. Is Immersive Debugger an AI tool? No. It is a runtime debugging tool used inside the headset. It is included here because it helps complete the development loop. BOTTOM LINE This stack is not about AI for the sake of saying AI. It is about tools that help Quest and Unity developers: Move faster Test easier Debug more clearly Keep projects cleaner Reduce repeated setup work Validate behavior inside the headset The practical story is simple: use AI tooling where it reduces friction, and use headset-first debugging where the real XR behavior actually happens. Degly
New Resource Guide Available: Simplifying Payouts for Developers!
Hello Developer Community, We’re thrilled to share our brand new resource guide: Payouts Made Simple for Developers! With 14% of Non-Technical Support Tickets being payments related, we wanted to find better ways to help solve common issues, so you can focus on building great apps and getting paid quickly for them. What’s It About? Whether you’re new to the platform or have managed payouts before, this guide is here to make payouts easy, clear, and hassle-free. It walks you step-by-step through everything you need to know—from setting up your account to receiving payments with minimal stress. Key Benefits Clear instructions for account setup, bank verification, and tax requirements Easy troubleshooting for common issues and payment delays Handy tips to help make sure your payouts are processed quickly Access to support resources right when you need them Get Involved! We want this guide to be as helpful as possible. Please check it out, try the suggestions, and let us know what you think! Your feedback helps us improve. If you spot something confusing or think we missed an important topic, drop a comment below! Already a payouts pro? Share your experience and best tips in the thread! Check out the guide here, and help us make Developer payouts smoother and simpler for everyone!PuzzleDeck: Spatial MR Puzzles with Full-Scale Reveals
I’ve been building a mixed reality puzzle experience for Meta Quest 3/3s and just got it live on the Store. Would love some testers and honest feedback. I’m part of a super small team of three that loves building immersive experiences and mapping digital content to the physical world. It’s called PuzzleDeck. You load different puzzle kits and after each one is complete you unlock something that’s only possible in XR. Build a Great White Shark and see what 6 metres looks like standing in your living room. The reveal was one thing I felt was missing from puzzle building and could be really interesting in XR. I also wanted to build something that my kids would have fun with too. The Ocean Giants Puzzle Kit (Shark, Whale, Orca) is the free launch collection. Would genuinely love feedback on pretty much anything and everything. https://www.meta.com/experiences/puzzle-deck/27000539009540439/
Exploring Body Tracking via Wi-Fi CSI – A Newbie's Proposal
Hi everyone! I’m new here in the community and I’ve been diving deep into how we can push the boundaries of standalone VR tracking. As a fan of the Quest ecosystem, I’ve been thinking about a challenge we all know: tracking parts of the body that are out of the cameras' line of sight. I’ve been researching Wi-Fi CSI (Channel State Information) and was wondering if we could use the wireless signal already present in the headset to help with body tracking. Since Wi-Fi signals are affected by human movement (even through walls or behind the back), could this data be used to complement the existing IMU and optical tracking? The idea would be to use the CSI amplitude and phase changes as a secondary data layer to "guess" limb positions when the cameras can't see them. I know it’s a technical challenge, but I’d love to hear from more experienced devs here: Does the current Quest hardware allow low-level access to CSI data for this kind of processing? Could this be a viable way to achieve "Full Body Tracking" without external sensors in the future? I'm just starting to develop this concept and would appreciate any feedback or pointers to existing documentation! Best regards, Vinícius (Jurusbango)Proposta: Rastreamento Corporal Total via Wi-Fi
Subject: Proposal: WiFi-based Full Body Tracking using CSI (Channel State Information) Message: Hi Meta Dev Team, I would like to propose a feature that could revolutionize body tracking on Meta Quest headsets without requiring external trackers or extra cameras: WiFi-based Motion Sensing using CSI (Channel State Information). The Concept: Every time a person moves between a WiFi transmitter (router) and a receiver (Quest), the signal undergoes phase and amplitude distortions. By accessing the CSI data from the Quest’s WiFi chipset, we can analyze these signal patterns to identify body posture and movement in real-time. Technical Implementation: Signal Analysis: Utilize the 5GHz/6GHz signal fluctuations to map the user's silhouette and limb positions. Machine Learning Integration: Use a lightweight neural network to translate CSI "shadows" into skeletal data, similar to how researchers have successfully used WiFi for "through-wall" sensing. Hybrid Tracking: Combine this WiFi data with the existing Inside-Out tracking and IMU data to fill in the gaps when the controllers or legs are out of the cameras' field of view. Why this is a game-changer: Zero Cost for the User: No need for Vive trackers or Tundra trackers. Privacy: It doesn't rely on optical images of the room, just radio frequency patterns. Lower Latency: Direct processing of signal data can be extremely fast on modern SOCs. I believe this would make Full Body Tracking accessible to everyone and put the Quest even further ahead in the VR market. Best regards, Vinícius
Model Everything, I Guess?
Alright, Meta AI, hear me out. A little background: I'm a small-scale web developer, videographer, and photographer with about 10 years of experience. Over the past year, I took something of a gap year to dive into AI and research the technology. This led me to a project that's in line with my expertise: real estate and architectural photography, which is basically about capturing spaces. My idea is to train a model using a combination of Instagram & Facebook images (with their tagged locations, of course) and 3D terrain models from multi-date satellite images (In the future: add property listing images). By combining these, we could create a virtual, living, breathing digital twin of the entire real world. This model would map both the outside world and most public indoor spaces, likely requiring a staggered rollout. I know this would require a metric ton of servers. I'm currently tinkering with a small-scale prototype, but I don't have the resources to scale this monster. The biggest limiting factor is being from South Africa (born in '98). Our government isn't exactly tech-friendly; instead of encouraging new tech, they create roadblocks and regulations that stifle innovation, all to protect corrupt, archaic monopolies. It's infuriating. Meta already has all the data needed for this model. So, if anyone at Meta AI sees this, please build this thing. And hey, maybe hook a man up with a tiny royalty? 😉 P.S. I would love to build this with you. Seriously, hit me up. Kind Regards, T South Africa
