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Bezelbub MCP

by cwooddgrversion 0.4.0i★ –iRuns on your computer
Registry nameio.github.cwooddgr/bezelbub-mcp

Install

Overview

Description from the maker (original English)

Frame screenshots and screen recordings in Apple device bezels (device mockups). macOS only.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Other

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • npmNode.js installed (for the npx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "bezelbub": {
      "command": "npx",
      "args": [
        "-y",
        "@dgr_labs/bezelbub-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add bezelbub -- npx -y @dgr_labs/bezelbub-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "bezelbub": {
      "command": "npx",
      "args": [
        "-y",
        "@dgr_labs/bezelbub-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "bezelbub": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "@dgr_labs/bezelbub-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account cwooddgr, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Otheri

  • More stars than 0% of the other 32715 servers in this category
  • Published to the registry more recently than 66% of the other 32715 servers in this category
  • Basic checks equal to or better than 100% of the other 32715 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Bezelbub MCP safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.4.0) reached the registry 20 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Spec Driven Development, Remote Desktop Commander, First Sale Scout

Alternatives

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Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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by formulahendry

MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.

Runs on your computer★ 440MITUpdated 14 months ago
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Remote Desktop Commander

by desktop-commander

Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.

Runs in the cloud★ 211Updated 2 days ago
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First Sale Scout

by firstsale.pro

Playbooks and a 14-day checklist for founders winning their first paying customers.

Runs in the cloudUpdated today
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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Bezelbub

Bezelbub puts your screenshots and screen recordings inside realistic Apple device bezels, so you get pixel-accurate device mockups for iPhone, iPad, Mac, and Apple TV as framed images and videos. You can use it three ways:

  • As a macOS and iOS app. Drop in a screenshot or a video, and Bezelbub picks the matching device and frames it.
  • As a headless command-line tool, bezelbub (brew install cwooddgr/tap/bezelbub). Frame a screenshot from a script, add a device frame to a screen recording, or export a transparent HEVC-with-alpha video with a VP9/WebM copy for Chrome and Firefox. We built it for shell scripts, CI, and AI agents. Jump to the CLI docs.
  • As a Swift package with no UI, `BezelbubKit`, if you want the framing engine inside your own tool.

Get Bezelbub on the App Store for Mac, iPhone, and iPad.

What you can do with it

  • Let it find the device. Drop in a screenshot or video and you get the right bezel. We recognize iPhones and iPads by their exact resolution. For Macs, iMac, Studio Display, and Apple TV we recognize the capture size of each macOS display zoom setting, from "Larger Text" to "More Space", so you can take the capture at any zoom level. If we don't have a size on file, we fall back to matching by aspect ratio. When several models share a panel, you pick from all of them. Load another screenshot for the same device and your device and color choices stay put.
  • Drag and drop on the Mac. Drop a screenshot or screen recording on the window or the Dock icon.
  • Paste on the Mac. Copy a screenshot and press ⌘V, or use Edit ▸ Paste.
  • Photos and the share sheet on iPhone and iPad. Import from Photos, or send an image to Bezelbub from any app's share sheet.
  • Frame videos. Export MOV and MP4 screen recordings with the bezel on top, with the audio kept.
  • Export transparent video. Save a framed recording with a fully transparent background as HEVC-with-alpha in a QuickTime .mov, ready to lay over any web page or presentation.
  • Fix rotation. Rotate a video that came in sideways. Option-click to go the other way.
  • Pick the color. Every color Apple ships for each device.
  • Set the export size. Change the width, the height, or the scale before saving. Images go up to 16,384 px and videos up to 7,680 px.
  • Copy or save. Copy a framed image to the clipboard, save it as PNG, or export a framed video as MOV or MP4.
  • Portrait or landscape for iPhone and iPad.

Devices

  • iPhone: 14, 14 Plus, 14 Pro, 14 Pro Max, 15, 15 Plus, 15 Pro, 15 Pro Max, 16, 16 Plus, 16 Pro, 16 Pro Max, 17, 17 Pro, 17 Pro Max, Air, 18 Pro, 18 Pro Max
  • iPhone Duo: three views, each its own device. Frame the inner display with the phone open (iphoneduo), the outer display with the phone closed (iphoneduoouter), or the outer display with the phone open and seen from the back (iphoneduoouteropen), in portrait or landscape
  • iPad: iPad, iPad (A16), iPad Air 11"/13" M2, iPad Air 11"/13" M4, iPad mini, iPad mini (A17 Pro), iPad Pro 11"/13" M4, iPad Pro 11"/13" M5
  • Mac: MacBook Air 13", MacBook Air 13"/15" M5, MacBook Pro 14", MacBook Pro 16", MacBook Pro 14"/16" M5, MacBook Neo, iMac 24", iMac 24" M4, Studio Display (2026). Any display zoom setting works. The Studio Display bezel covers the XDR too, because Apple ships identical art for both
  • Apple TV: Apple TV 4K, from 1080p or 4K screenshots

The bezelbub command-line tool

With bezelbub you can frame screenshots and screen recordings from a shell script, a CI pipeline, or an AI agent. There is no GUI and nothing ever prompts you. Every input is a flag with a sensible default, you can ask for JSON output, and when something goes wrong you get a distinct nonzero exit code plus a concrete suggestion on stderr (valid ids, matching devices, nearest screen sizes), so one failed call tells you how to fix the next one.

Install it with Homebrew:

brew install cwooddgr/tap/bezelbub
Quick start
# Frame a screenshot. We detect the device from its pixel size.

bezelbub frame --input shot.png # writes shot-framed.png

Frame a screen recording (.mov/.mp4/.m4v). Audio is kept; you get an MP4.

bezelbub frame --input demo.mp4 # writes demo-framed.mp4

Transparent video: HEVC-with-alpha in a QuickTime .mov

(plays in Safari and Apple frameworks; the background is fully transparent)

bezelbub frame --input demo.mp4 --background transparent # writes demo-framed.mov

Add a VP9/WebM copy with alpha for Chrome and Firefox (needs ffmpeg on PATH)

bezelbub frame --input demo.mp4 --background transparent --webm

writes demo-framed.mov and demo-framed.webm

List device ids, colors, and screen sizes

bezelbub devices [--json]

Which devices fit this screenshot or recording?

bezelbub devices --input shot.png # or demo.mp4, or --dimensions 1206x2622

Or spell everything out

bezelbub frame --input shot.png --device iphone17pro \ --color "Cosmic Orange" \ --orientation landscape \ --background "#1D1D1F" \ --output-size 50% \ --output framed.png --json

frame is the default subcommand, so bezelbub --input shot.png works too.

How device detection works

Leave out --device and we work out the device from the input's pixel dimensions. For iPhones and iPads that means an exact match on screen resolution, within a pixel. For Macs, iMac, Studio Display, and Apple TV it means an exact match on capture size: every macOS display zoom setting captures at a known pixel size per model, so a 3420×2214 screenshot can only have come from a 15" MacBook Air, whatever zoom it was taken at. Sizes we don't have on file, such as external monitors or downscaled recordings, fall back to aspect-ratio matching. When you frame a display capture, we scale it to fit the bezel's screen.

Detection succeeds when exactly one device matches. If several models share the size, the error lists them so you can run again with --device . If nothing matches, we suggest the nearest devices by aspect ratio. To check before framing anything, run bezelbub devices --input or bezelbub devices --dimensions WxH.

Transparent video and WebM

Pass --background transparent with a video input and you get HEVC with an alpha channel in a QuickTime .mov instead of an MP4: a device-framed recording with a fully transparent background, ready to lay over anything. Safari and Apple's frameworks (AVFoundation, AppKit, UIKit) play HEVC-with-alpha. Chrome and Firefox don't decode it.

For those browsers, add --webm and you also get a VP9/WebM copy that keeps the alpha channel. To make it we render a temporary ProRes 4444 master and hand that to ffmpeg, which must be on your PATH. We deliberately don't hand ffmpeg the HEVC .mov: ffmpeg builds older than 8.0 can't decode HEVC's alpha layer and silently write an opaque WebM. Version 8 and later decode it fine, but the ProRes route works on any build. Serve both files, with the .mov first:

<video autoplay loop muted playsinline>

The order matters. Safari can play VP9/WebM but drops its alpha channel, so if you list the WebM first, Safari shows your transparency as solid black. With the .mov first, Safari takes the HEVC-alpha file, while Chrome and Firefox skip video/quicktime and fall through to the WebM.

If you pass --output for a transparent export, the path must end in .mov. The WebM lands beside it with a .webm extension.

Flags
bezelbub frame --input <path> [options]

bezelbub devices [--input | --dimensions WxH] [--json]

Options for frame:

FlagWhat it does
--input, -iThe screenshot (PNG, JPEG, HEIC) or video (.mov, .mp4, .m4v, chosen by extension). Required.
--device, -dA device id from bezelbub devices. Leave it out to detect from pixel size.
--color, -cA color name or id, case-insensitive. Defaults to the device's default color.
--orientationportrait, landscape, or auto (the default, taken from the input's shape).
--backgroundA hex color (#RRGGBB or #RRGGBBAA) or transparent. Defaults to transparent for images and black for video. transparent on a video switches the output to HEVC-with-alpha .mov.
--output-sizeScale the result, keeping the bezel's aspect: a width (1920), an exact WxH that matches the aspect, or a percentage (50%). Images go from 16 to 16,384 px, videos from 16 to 7,680 px.
--output, -oWhere to write the result. Defaults to -framed.png, .mp4, or .mov beside the input.
--webmAlso write a VP9/WebM copy with alpha. Video with --background transparent only; needs ffmpeg on PATH.
--jsonPrint a JSON result on stdout instead of a text summary.

devices lists the whole catalog (ids, display names, colors, orientations, screen sizes, and each display device's known capture sizes), or narrows it to the devices that fit an --input file or a bare --dimensions value. Filtering always exits 0. An empty matches array is the signal that nothing fits, and nearest (by aspect ratio) fills in when that happens.

JSON output

frame --json prints one object:

{

"color" : "Cosmic Orange", "device" : "iphone17pro", "height" : 2760, "kind" : "image", "orientation" : "portrait", "output" : "/path/shot-framed.png", "width" : 1350 }

kind is "image" or "video". For video you also get "transparent": true|false and, when --webm ran, the "webm" output path. devices --json prints an array of {id, displayName, defaultColor, colors, landscapeOnly, hasPortraitBezel, screenWidth, screenHeight, captureSizes}. With --input or --dimensions it prints {width, height, matches, nearest} using the same device objects, and nearest is filled only when matches is empty.

Exit codes

Each failure type has its own code, so a script can branch without parsing stderr:

CodeMeaning
0Success
1A flag value we couldn't parse, such as a malformed --background or --output-size
2Unknown, ambiguous, or undetectable device. stderr lists the candidates.
3Unknown color. stderr lists the device's valid colors.
4We couldn't read the input image or video
5Compositing or video export failed
6We couldn't write the output
7The --webm conversion failed because ffmpeg is missing from PATH or returned an error
64Malformed arguments (the standard EX_USAGE)
For AI agents

We built the CLI for non-interactive, programmatic use, by LLM agents (Claude Code, MCP tool wrappers, CI bots) as much as by people:

  • Nothing prompts. Every input is a flag with a default, so a call either finishes or fails right away.
  • Both subcommands take `--json` and return the shapes shown above.
  • Errors tell you how to fix them. stderr includes did-you-mean device and color ids, the devices that fit the input's pixel size, and the nearest sizes, so an agent can correct the next call without a human.
  • Exit codes 2 through 7 name the failure type (table above), so an agent can branch without reading text.
  • Pipes stay clean. We only print video-export progress to stderr when it's a TTY, so captured output stays parseable.
  • A typical agent flow: run bezelbub devices --input shot.png --json to check the match, then bezelbub frame --input shot.png --json and read output from the result.

This repo also includes a ready-made Claude Code skill at skills/bezelbub-cli/ that teaches an agent the whole wor

Only the beginning is shown; read the rest in the repo

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