visor-mcp
Allows control and monitoring of Meta Quest headsets, including screenshots, app management, performance monitoring, and log collection.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@visor-mcpTake a screenshot of my headset"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Visor
Cross-platform Quest developer toolkit — an open source alternative to Meta Quest Developer Hub (MQDH) that runs on Linux, macOS, and Windows (MQDH is Windows/Mac only, so Linux users had nothing), plus something MQDH doesn't have on any platform: an MCP server that lets AI coding agents — Claude Code and any other MCP-compatible client — see and control your headset.
Four layers, one library:
Layer | Command | What it does |
Python library |
| Quest-aware ADB wrapper: devices, apps, capture, logs, performance |
MCP server |
| 29 |
CLI |
| MQDH-like functionality from the terminal |
Web dashboard |
| Live instrument panel: perf charts, viewport, logs, app/file management |
Requirements
Python 3.10+ on Linux, macOS, or Windows
adbon your PATH:Linux:
sudo apt install android-sdk-platform-tools(orsudo pacman -S android-tools)macOS:
brew install android-platform-toolsWindows:
winget install --id Google.PlatformTools(or download platform-tools)
A Quest with developer mode enabled, connected via USB (accept the debugging prompt in the headset) or wireless ADB
Optional:
ffmpegfor the dashboard's live video view,scrcpyfor casting (both available via the same package managers)
Related MCP server: ADB MCP Server
Install
pip install visor-dev # provides the `visor` command; from source:
git clone https://github.com/chisomobanzi/visor && cd visor && pip install .CLI quickstart
visor devices # list connected headsets
visor info # battery, storage, firmware, thermal
visor connect-wireless # unplug the cable, stay connected
visor install ./my-game.apk # sideload a build
visor launch com.my.game
visor apps # sideloaded apps
visor screenshot # auto-wakes a sleeping headset
visor record 30 # 30s video
visor cast # scrcpy casting
visor logs --tag Unity --level D # filtered logcat
visor logs --grep NullReference -f # follow live
visor crash-logs com.my.game # parsed crash/ANR reports
visor perf # CPU/memory/thermal/battery snapshot
visor perf --monitor 30 # timeseries
visor thermal # per-sensor temps with throttle warnings
# Profiling (see "Performance profiling" below)
visor perf record -t 60 # record a session while you play
visor perf report session.json # summary + bottleneck diagnosis
visor perf diff before.json after.json
visor bench com.my.game # cold-start benchmark
visor trace -t 10 # perfetto trace -> ui.perfetto.dev
visor push ./file /sdcard/ · visor pull /sdcard/f ./ · visor ls /sdcard/Multiple devices? Add --device <serial>.
AI assistant integration (MCP)
visor-mcp is a standard Model Context Protocol server over stdio, so it works with any MCP-compatible client — Claude Code, OpenAI's Codex CLI, Cline, Continue, Cursor, and agent frameworks built on the MCP SDKs (including ones driving open-source models). It's primarily developed and tested against Claude Code, but nothing in it is Claude-specific: it exposes plain MCP tools and standard content blocks.
The server is a single command, visor-mcp, that speaks MCP over stdio and takes no arguments — register it however your client expects.
Claude Code:
claude mcp add quest -- visor-mcpMost other clients (Cursor, Cline, Continue, Claude Desktop, …) use a JSON config:
{
"mcpServers": {
"quest": {
"command": "visor-mcp"
}
}
}Codex and some others use their own config file, but the essentials are the same everywhere: run visor-mcp, no args, stdio transport.
Then ask your assistant things like:
"Take a screenshot of my headset — what's on screen?" — clients that support image tool results (like Claude Code) display the actual image; text-only clients still get every other tool
"Install this build, launch it, and watch the logs for exceptions while I test"
"Why did my app crash? Pull the crash log and explain the stack trace"
"Monitor performance for 60 seconds while I play, then tell me if I'm thermal throttling"
Tools exposed: quest_devices, quest_info, quest_screenshot, quest_install, quest_uninstall, quest_launch, quest_stop, quest_app_list, quest_app_info, quest_app_memory, quest_clear_data, quest_logs, quest_logs_stream, quest_crash_logs, quest_performance, quest_monitor, quest_thermal, quest_frame_timing, quest_perf_session, quest_perf_diff, quest_launch_benchmark, quest_trace, quest_screen_record, quest_push, quest_pull, quest_files, quest_connect_wireless, quest_set_refresh_rate, quest_tracking.
Web dashboard
visor ui # opens http://127.0.0.1:7700Overview (battery/thermal lens gauges, tracking status), viewport with real-time live video (H.264 off the device via screenrecord, transcoded to an MJPEG stream — requires ffmpeg), performance charts sampled every 2.5s, filterable log viewer with crash reports, app management (install APK by upload, launch/stop/clear/uninstall), and a device file browser. Localhost-only by design.
Library
from visor import adb
quest = adb.discover_devices()[0]
adb.install_apk("build.apk", quest.serial)
adb.launch_app("com.my.game", quest.serial)
for entry in adb.logcat_stream(quest.serial, level="E"):
print(entry.tag, entry.message)All functions raise typed errors (DeviceUnauthorizedError, DeviceNotFoundError, …) with actionable messages instead of raw ADB stderr.
Performance profiling
Visor is a full VR profiler built on the per-second VrApi metrics the
Quest runtime logs for any rendering VR app: FPS vs target, stale frames,
CPU/GPU dynamic levels + clocks + utilization (including worst core), app
GPU time vs frame budget, and free memory — plus periodic memory anatomy
(dumpsys meminfo, where graphics allocations dominate) and thermal
snapshots.
Sessions are the core primitive: record one while you play
(visor perf record, the dashboard's ● RECORD, or the quest_perf_session
MCP tool), get a summary and an evidence-based bottleneck diagnosis —
GPU-bound, CPU-bound (single-thread vs parallel), thermal throttling
(including silent clock clamping), memory pressure (lmkd kills), hitching
(bursts with headroom), or memory growth — each with concrete
recommendations. Sessions are JSON files; diff two of them to verify an
optimization (visor perf diff / quest_perf_diff).
The dashboard's Performance tab is a live workspace: FPS chart with target line and stale-frame dots, app GPU time vs budget, utilization, clock levels, memory series, skin temperature with throttle threshold, and event annotations (level changes, thermal transitions, lmkd kills).
For the "what exactly blocked this frame" tier: visor trace captures a
perfetto system trace (scheduling/clocks/graphics; open at ui.perfetto.dev),
and visor bench measures cold-start times.
Notes: VR frame metrics only flow while the app is rendering — a
sleeping display pauses everything (visor auto-wakes it), and 2D panel
apps fall back to gfxinfo. Battery current draw isn't readable on OS
v14+, so drain is inferred from level over longer sessions.
Notes on Quest OS v14+
/sys/class/thermaland batterycurrent_noware permission-denied over ADB; visor reads thermals fromdumpsys thermalserviceinstead (45 sensors on Quest 3).Screenshots of a sleeping headset return nothing; visor auto-wakes the display via the
prox_closebroadcast and restores the proximity sensor afterwards.Screenshots are side-by-side stereo; the MCP/UI return the left eye for readability (full stereo PNG is kept on disk).
Development
python -m venv .venv && .venv/bin/pip install -e ".[dev]"
.venv/bin/pytestTests use captured real-device output as fixtures — no headset needed.
License
MIT
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