原型 · 预览版:收录官方注册中心里的全部服务器,每 30 分钟同步一次。评价和账户功能将在后续阶段推出。
PopNx MCP为使用 AI 的人准备的 MCP 服务器 · 用大白话讲清楚

Promoshot

作者:GarAlex版本 0.4.7i★ –i在你的电脑上运行
注册名称io.github.GarAlex/promoshot

安装

概览

作者提供的说明(英文原文)

Headless MCP: author and render PromoShot .promo video projects (stills, GIFs, video).

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

  • 连接方式: 在你的电脑上运行
  • 传输方式: stdio
  • 分类: 设计、图片与音频

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

  • 基础检查:1 项中通过 1 项
  • 在你的电脑上运行,拥有你的用户账户的权限(文件、网络、应用)。
  • 注册中心没有列出需要填写的密钥。

你需要

你用的是哪个应用?

在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json

{
  "mcpServers": {
    "promoshot": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/garalex/promoshot-mcp:v0.4.7"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add promoshot -- docker run -i --rm ghcr.io/garalex/promoshot-mcp:v0.4.7

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json

{
  "mcpServers": {
    "promoshot": {
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/garalex/promoshot-mcp:v0.4.7"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

{
  "servers": {
    "promoshot": {
      "type": "stdio",
      "command": "docker",
      "args": [
        "run",
        "-i",
        "--rm",
        "ghcr.io/garalex/promoshot-mcp:v0.4.7"
      ]
    }
  }
}

浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。

这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上,无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。

它能做什么

它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过 GitHub 账户 GarAlex 验证,该账户拥有此仓库

  • … 尚未检查

    仍在维护

    我们还没有从 GitHub 读取这个仓库

  • … 尚未检查

    有许可证

    我们还没有从 GitHub 读取这个仓库

  • – 不适用

    端点有响应

    它在你的电脑上运行,没有互联网端点

  • – 不适用

    使用 OAuth 登录

    在你的电脑上运行,改用本地设置

  • … 尚未检查

    工具描述中没有隐藏指令

    它在你的电脑上运行;我们只能读取互联网端点的工具列表

与“设计、图片与音频”中的其他服务器比较i

  • 星标数多于此分类中其他 2753 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2753 个服务器的 77% 更新
  • 基础检查结果等于或优于此分类中其他 2753 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。

常见问题

Promoshot 安全吗?

它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。

它需要哪些密钥或代码?

注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端?

它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(0.4.7)于9天前进入注册中心。

哪些应用可以使用它?

支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Docker。

有什么可以替代它?

同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server

替代选择

同一分类中其他作者的服务器,按星标数排序。

如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Figma Context MCP

作者:GLips

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

在你的电脑上运行★ 16,165MIT5个月前更新
安装

Claude Real Video

作者:HUANGCHIHHUNGLeo

Let any LLM watch a video locally — and search everything it has ever watched.

在你的电脑上运行★ 2,284MIT2个月前更新
安装

Figma MCP Server

作者:figma

The Figma MCP server brings Figma design context directly into your AI workflow.

在云端运行★ 2,15213个月前更新
安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

promoshot

See it work: demo.md — technique prompts and open-ended creative briefs, each given to a fresh agent with only the skill and the MCP, its result beside the hand-built reference. The suite is in demos/.

The rendering engine behind PromoShot (App Store), and an open implementation of its project format. A .promo project is a folder — metadata.json plus its media — and this workspace is everything needed to validate, inspect, and render one to stills, image sequences, or mp4 with mixed audio: no app attached, byte-for-byte the same compositor the apps ship.

The design bet is that the format is the interface. An assistant, a script, or a person writes metadata.json; the engine renders it the same everywhere — the Mac and iOS apps (Metal + VideoToolbox), this repo's CLI, or a headless Linux box with no GPU at all (wgpu on lavapipe, ffmpeg as a subprocess). The format has three faces behind one truth: an authoring subset with four validated recipes (promo schema), the full document (--full), and a types-only JSON Schema generated from the parser's own structs (--types) — and the parser the validator runs is the parser the renderers use, so "validates" means "renders".

Not the other PromoShot

This is the open engine (and App Store app) for [PromoShot](https://promoshot.app) by Alexander Garmash — a full layer / keyframe / timeline editor for screen recordings, video, and photos (Mac; iPhone and iPad open the same .promo projects).

It is not the similarly named App Store apps that turn screenshots into template videos (for example “PromoShot: Screenshot to Video”). If you want keyframes, masks, GPU compositing, and an open .promo format, you want this one: promoshot.app · App Store.

Product listing / PAD

Consumer apps: promoshot.app · App Store. Software directories can ingest this PAD 4.0 file:

https://raw.githubusercontent.com/GarAlex/promoshot/main/promoshot.pad.xml

Crates

CrateWhat it owns
promo-modelThe format: wire structs, migrations, palette roles, schema.md
promo-timelineTimeline math: keyframes, trims, attachments, waits, validation
promo-gpuwgpu compositing: quads, borders, letterbox, vectors, color conversion
promo-textCaption shaping and effects (cosmic-text)
promo-enginePreview/export orchestration, frame cache, memory governor, PCM mixer
promo-mediaDecoder/encoder trait registry; ffmpeg-subprocess backend + conformance suite
promo-editorThe document's edit vocabulary: commands with undo, the wizard's arrangement, theme rules — what promo_apply and promo_slideshow are built on
promo-clipromo — render a project from the command line
promoshot-mcpMCP server over stdio, for agents

Build and verify

./check-all.sh          # fmt, clippy -D warnings, all tests, release build

Rendering video needs ffmpeg (and ffprobe) on PATH — frames are composited on the GPU and piped to it raw; ffmpeg only decodes and encodes. On a headless Linux machine, mesa-vulkan-drivers (lavapipe) is enough of a GPU.

Headless Linux, no GPU

The Linux release tarball carries its own CPU renderer: a lavapipe/ folder (Mesa's lavapipe, its libraries and a Vulkan loader; licences in lavapipe/NOTICES.txt) beside promo. Keep the folder next to the binary and a machine with no Vulkan driver at all — a fresh container, or a redeploy that dropped mesa-vulkan-drivers — still renders. promo picks, in order: a real GPU; the system's lavapipe; the bundled lavapipe (saying so once on stderr); SwiftShader, with a warning, since it is 10–50× slower than lavapipe. With none of them it lists what it tried and the fix (sudo apt-get install -y mesa-vulkan-drivers libvulkan1). PROMO_LAVAPIPE= points at the folder elsewhere; PROMO_LAVAPIPE=off never uses it. The binaries need glibc 2.39 (Ubuntu 24.04, Debian 13). A machine with no fonts at all still renders: text falls back to a built-in face (Tuffy) with a warning; install fonts-dejavu-core and fonts-liberation for real ones.

What a CPU costs, measured on a 703-frame 1080×1920 reel with narration:

Rendererpromo video
Mac GPU (Apple silicon, Metal)13.7 s
lavapipe, 8 cores18.9 s
lavapipe, 2 cores77 s
lavapipe, 1 core179 s

(lavapipe in an amd64-emulated ubuntu:24.04 container; SwiftShader took about half an hour on a comparable reel.)

promo video survives being killed. It encodes in segments (10 s of video each; --segment ) into .promo-parts/ beside the output, and the same command run again skips the finished segments and goes on from there, saying how many it found. The segments are joined without re-encoding, the soundtrack is mixed once for the whole range and muxed in at the join — no edge in the sound, in sync to the sample — and the folder is removed on success. The folder is keyed by a digest of the project's files and the render settings, so an edited project starts over instead of reusing stale segments. --from/--to take seconds (12.5) or frames (375f), to split a long render into chunks.

The CLI

cargo build --release -p promo-cli     # -> target/release/promo

promo schema # authoring subset + recipes; --full, --types promo validate [--strict] # "NOT OK" lists what will not render; --strict exits 1 on any finding promo inspect # canvas, layers, missing media, undefined colours promo upsert-keyframe --args '{"layer":"bg","time":2,"zoom":1.2}'

the MCP authoring tools as verbs (init, upsert-layer,

upsert-keyframe, apply, slideshow, explain, diff)

promo still --out f.png --time 2.5 promo frames --out frames/ --fps 30 --from 0 --to 4 promo video --out out.mp4 --fps 30 # resumable; --from/--to 12.5 or 375f

Add --json to any project command for machine output — one object on stdout, errors included, exit codes unchanged.

promo video mixes the soundtrack the apps would: trims and media cuts, held frames, speed with pitch preserved, keyframed volume, a focused narration ducking everything under it, and only the audio tracks the project keeps.

Headless renders are CLEAN — no watermark, and no license, serial or key will ever be asked for. (The Mac and iOS apps watermark free-tier renders; that is their App Store Pro line, and it stays on their side of the fence.)

The MCP server

promoshot-mcp speaks Model Context Protocol over stdio, so any MCP client can author, inspect and render projects. It owns no rendering code — every render shells to promo (found next to the executable, or on PATH, or via --promo), so the CLI stays the single contract.

Connect an agent

Two pieces: the MCP server (tools) and the skill (workflow). Neither is vendor-specific. Agents do not find this repo by themselves.

The apps open what this engine writes from PromoShot 3.0 on. The App Store's 2.3.1 reads projects up to minReaderVersion 17 (no nested compositions, no 3D) and cannot be launched with --mcp-stdio.

1. Build — or don't

cargo build --release -p promo-cli -p promoshot-mcp

binaries: target/release/promo target/release/promoshot-mcp

scripts/install-local.sh # …and on PATH, linked from target/release,

so every later build is what runs

No Rust toolchain? Grab the prebuilt pair from Releases (linux-x64, macos-arm64; each asset's sha256 is on the release), or pull the image: docker pull ghcr.io/garalex/promoshot-mcp — both carry promo and promoshot-mcp together.

Put both on PATH, or pass --promo to the server. Rendering video also wants ffmpeg/ffprobe on PATH. promo skill install then puts the agent skill where every agent tool on the machine reads it — the shared ~/.agents/skills (Codex, Gemini CLI, Cursor, GitHub Copilot, Grok Build) and the own folder of each tool found that reads only its own (Claude Code, Antigravity); promo skill prints it.

2. MCP (required for tools)

Claude Code / Cursor / any mcp.json:

{

"mcpServers": { "promoshot-headless": { "command": "/ABS/PATH/target/release/promoshot-mcp", "args": ["--workspace", "/ABS/PATH/Promo", "--root", "/ABS/PATH/Promo"] } } }

--workspace is where new projects go; --root fences which projects the server will touch — pointing both at one folder is the tidy setup. Both optional. --log appends one line per tool call — when, which tool, how many milliseconds, how it went — for a session's own accounting; the demo pages are built from it.

Client one-liners:

# Claude Code

claude mcp add promoshot-headless /ABS/PATH/target/release/promoshot-mcp

Grok Build

grok mcp add promoshot-headless -- /ABS/PATH/target/release/promoshot-mcp \ --workspace /ABS/PATH/Promo --root /ABS/PATH/Promo grok inspect # confirms the server registered

Docker — the host needs nothing but docker (details below)

docker build -t promoshot-mcp .

then command: docker, args: ["run","-i","--rm","-v","/ABS/PATH/Promo:/projects","promoshot-mcp"]

On a Mac with PromoShot 3.0 installed, the app is a server too — the same tools, with the person's open document, undo and approvals behind them. Switch Automation on in PromoShot's Settings, then register the app itself; it launches when the client starts it:

claude mcp add promoshot -- "/Applications/PromoShot.app/Contents/MacOS/PromoShot" --mcp-stdio

Settings ▸ Automation shows that line with this Mac's own path, and the URL form for clients that take one. promoshot names the app and promoshot-headless the binary, so both can be registered side by side; the skill asks which to use when both are there.

3. Skill (the workflow)

Same file everywhere: skill/SKILL.md.

REPO=https://github.com/GarAlex/promoshot

git clone --depth 1 $REPO /tmp/promoshot

Claude Code (Grok Build also scans this folder)

mkdir -p ~/.claude/skills/promoshot cp /tmp/promoshot/skill/SKILL.md ~/.claude/skills/promoshot/SKILL.md

Grok Build explicit path

mkdir -p ~/.grok/skills/promoshot cp /tmp/promoshot/skill/SKILL.md ~/.grok/skills/promoshot/SKILL.md

OpenAI Codex / many others

mkdir -p ~/.agents/skills/promoshot cp /tmp/promoshot/skill/SKILL.md ~/.agents/skills/promoshot/SKILL.md

Cursor project (in the repo the user is editing, not this engine repo)

mkdir -p .cursor/rules cp /tmp/promoshot/skill/SKILL.md .cursor/rules/promoshot.md

or: mkdir -p .agents/skills/promoshot && cp SKILL.md there

Any agent that reads instructions can be handed the file directly; it assumes only these tools (or the CLI).

4. Verify — ask the agent for a render:

Render examples/ProductCard.promo to a still at 3s.

One promo_validate, one promo_render_still, and a device-framed app demo comes back as a path. From there, "make me a promo for " is the loop the skill teaches.

The tools

Tools: promo_schema (authoring subset + four validated recipes; promo_schema_full is the whole format; promo_schema_types is the format as a generated, types-only JSON Schema — also checked in at docs/promo.schema.json for $schema editor au

只显示了开头部分;其余内容请在仓库中阅读

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