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

Mochify

作者:getmochify版本 1.6.2i★ –i电脑或云端
注册名称app.mochify/mochify

安装

概览

作者提供的说明(英文原文)

Image and PDF toolkit: convert to AVIF/WebP/JXL, resize, crop, remove backgrounds, optimize PDFs.

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。

安装

选择你使用的 AI 应用,然后复制设置。

安装之前

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 …”。

适用于网页版、桌面版和手机版 Claude:

  1. 打开 Settings → Connectors
  2. 点击 Add custom connector
  3. 粘贴下面的地址,然后点击 Add
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Add2https://…3
https://mcp.mochify.app/mcp

在终端中运行这条命令

claude mcp add --transport http mochify https://mcp.mochify.app/mcp

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": {
    "mochify": {
      "url": "https://mcp.mochify.app/mcp"
    }
  }
}

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": {
    "mochify": {
      "type": "http",
      "url": "https://mcp.mochify.app/mcp"
    }
  }
}

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。

ChatGPT 只能连接互联网上的服务器:

  1. 打开网页版 ChatGPT → Settings → Connectors (Apps)
  2. 点击 Create 或 Add(部分套餐需要先在 Advanced 中开启 Developer mode)
  3. 粘贴下面的地址,起个名字,然后保存
  4. 如果要求登录,请登录作者的服务
SettingsConnectors1+ Create2https://…3
https://mcp.mochify.app/mcp

菜单名称可能因套餐和版本不同而略有差异。

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

我们还没有读取这个服务器的工具列表;我们会轮流检查各个端点。

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6日

  • ✓ 通过

    作者与仓库一致

    注册名称已通过域名 mochify.app 验证(注册中心会核实域名所有权)

  • … 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

  • … 尚未检查

    端点有响应

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    使用 OAuth 登录

    尚未检查;我们会轮流检查各个端点

  • … 尚未检查

    工具描述中没有隐藏指令

    尚未检查;我们会在检查端点时读取工具列表

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 2164 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2164 个服务器的 36% 更新
  • 基础检查结果等于或优于此分类中其他 2164 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

Mochify 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?

两种方式都可以:安装在你的电脑上,或者连接云端版本。

它还在维护吗?

GitHub 仓库最后更新于–,最新版本(1.6.2)于2个月前进入注册中心。

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。它通过 URL 连接,所以接受远程 MCP 服务器的应用也可以使用,例如开启开发者模式的 ChatGPT。

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。

mochify-cli

A command-line tool and MCP server for mochify.app — a fast, privacy-first image compression and conversion API powered by a native C++ engine.

Compress and convert images to modern formats (AVIF, JXL, WebP, Jpegli) from your terminal, work on PDFs, or give AI assistants like Claude direct access to the same engine over the Model Context Protocol — either as a local stdio server (mochify serve) or the hosted one at mcp.mochify.app, which needs no install at all.

Jump to: Installation · CLI usage · PDF processing · MCP server · Plans

Installation

macOS (Homebrew):

brew tap getmochify/mochify

brew install mochify

Windows (Scoop):

scoop bucket add mochify https://github.com/getmochify/scoop-mochify

scoop install mochify

Linux / WSL:

# x86_64

curl -L https://github.com/getmochify/mochify-cli/releases/latest/download/mochify-linux-x86_64 -o mochify chmod +x mochify sudo mv mochify /usr/local/bin/

arm64

curl -L https://github.com/getmochify/mochify-cli/releases/latest/download/mochify-linux-arm64 -o mochify chmod +x mochify sudo mv mochify /usr/local/bin/

Cargo (all platforms):

cargo install mochify

Requires Rust. Easiest option on Linux/WSL if you already have the toolchain.

Manual: All binaries at Releases.

From source:

cargo install --path .

Authentication

Sign in with your mochify.app account to unlock your full quota:

mochify auth login

This opens your browser, where you sign in and authorize the CLI. Credentials are saved automatically to ~/.config/mochify/credentials.toml — no environment variables or manual key copying required. Both the CLI and MCP server pick them up automatically.

On a machine without a browser (over SSH, say), sign in with a code instead — open the link it prints on any device and type the code:

mochify auth login --no-browser
mochify auth status   # check whether you're signed in

mochify auth logout # remove saved credentials

Without an account you get 3 images per batch (IP-based). With a free account: 25 images/month. Sign up at mochify.app.

CLI Usage

mochify [OPTIONS] <FILES>...
Options
FlagDescription
-t, --type Output format: jpg, png, webp, avif, jxl
-w, --width Target width in pixels
-H, --height Target height in pixels
--cropCrop to exact dimensions (saliency-guided)
--region Crop to a rectangle, as fractions 0–1 of the upright image from the top-left
--redact Hide areas: faces and/or ;-separated boxes x,y,w,h (same convention as --region)
--redact-style fill (solid black, default) or blur (cosmetic only)
-r, --rotation Rotation: 0, 90, 180, 270
-o, --output Output directory (default: same as input)
-n, --name Base name for the output file (without extension)
--clarityApply clarity (midtone contrast enhancement — crisper, more detailed look)
--remove-bgRemove the background (AI foreground isolation)
--background Composite colour for --remove-bg (white, #ff0000, …)
--keep-metadataPreserve EXIF/metadata (stripped by default)
-q, --quality Output quality 1–100 (default: automatic)
--smart-compressSaliency-guided quality — detail keeps more, flat areas less
--brightness Exposure, -100 (darkest) to +100 (brightest)
--optimize-for-webProgressive + 4:2:0 chroma — smallest file to serve
--losslessPixel-exact output (jxl, webp, png only)
--hdr [MODE]Ultra HDR gain map: preserve (bare flag) or generate
-p, --prompt Natural-language prompt — resolves all params automatically
-j, --jobs Files to process at once (default 4; 1 for strictly one at a time)
-k, --api-key API key override (or set MOCHIFY_API_KEY env var)
Examples
# Convert to AVIF

mochify photo.jpg -t avif

Resize and convert to WebP

mochify photo.jpg -t webp -w 800

Batch convert a folder to AVIF at 1200px wide

mochify ./images/*.jpg -t avif -w 1200 -o ./compressed

Natural-language prompt — let the AI pick the right params

mochify photo.jpg -p "convert to avif, 1200px wide" mochify photo.jpg -p "optimise for eBay" mochify photo.jpg -p "remove background and convert to WebP" mochify photo.jpg -p "resize to 50%, strip EXIF, keep as WebP"

Custom output name

mochify photo.jpg -t webp -n hero mochify product.jpg -p "optimise for Shopify" -n product-main

Pipe file paths from stdin

find . -name "*.jpg" | mochify -t webp -o ./out cat images.txt | mochify -p "convert to avif 1200px wide" -o ./compressed ls *.heic | mochify -t jpg

Quality

Quality is chosen automatically unless you say otherwise.

# Fixed quality

mochify photo.jpg -t webp -q 70

Let saliency pick it — detailed subjects keep more, flat areas less

mochify photo.jpg -t avif --smart-compress

Smallest file to serve from a web server

mochify photo.jpg -t webp --optimize-for-web

Brighten a dark photo

mochify photo.jpg --brightness 30

Pixel-exact

mochify scan.png -t webp --lossless

--lossless only works for jxl, webp and png — jpg and avif are rejected before the request goes out. It overrides -q and --smart-compress, and the output is usually larger than the input: lossless preserves pixels, not file size. A source that is already lossy (JPEG, AVIF, HEIC) comes back as the best lossy encode instead, since nothing can restore what that file discarded — the CLI says so when that happens.

Cropping to a region

--crop finds the subject itself. --region is for when *you* — or the AI assistant driving the MCP server — already know which part of the picture you want:

# The bottom-left quarter

mochify photo.jpg --region 0,0.5,0.5,0.5

A region, then sized: -w/-H apply to the cropped part

mochify photo.jpg --region 0.2,0.1,0.6,0.8 -w 800 -t webp

The four numbers are x,y,width,height as fractions of the image (0 to 1), measured from the top-left of the picture as it displays — the right way up, even for a phone photo stored sideways. Fractions rather than pixels so the same box works whatever size the image is viewed at. A value above 1 is refused before the request goes out, since that is almost always a box in pixels. The region is cut first: -w/-H, --crop, --rotation and --remove-bg all act on it. --verbose prints the pixel rectangle that was actually cut.

Over MCP this is how an assistant can crop to *content* — "crop to the feet", "just the logo": it looks at the image itself, picks the box, and Mochify only ever receives the four numbers.

Redaction

Hide faces, number plates, addresses or anything else before an image goes anywhere:

# Every face, found automatically

mochify family.jpg --redact faces

A number plate, as a box (fractions of the upright image, like --region)

mochify car.jpg --redact 0.38,0.71,0.24,0.08

Both, softened with a blur instead of a solid fill

mochify street.jpg --redact "faces;0.38,0.71,0.24,0.08" --redact-style blur

Separate entries with ; — the , belongs to the box. fill (solid black) is the default and the one to use for anything that must stay secret; blur is for the look of a blurred face, and blurred text or faces can sometimes be recovered.

Redaction always strips metadata (EXIF can hold a thumbnail of the original) and removes any HDR gain map (which holds the scene's structure), even if you asked to keep them. faces is best-effort — it can miss small faces and side profiles — so the CLI says when it found none. Check the output before sharing it.

HDR (Ultra HDR gain maps)

--hdr controls the Ultra HDR / ISO 21496-1 gain map that makes a photo render with real headroom on an HDR display.

ModeWhat it does
--hdr (or --hdr preserve)Keeps a gain map the source already has. Never invents one, so it does nothing to an SDR photo.
--hdr generateKeeps an existing gain map and synthesises one when the source is plain SDR. This is the one for "make it HDR".

Only jpg output can carry a gain map (jxl carries HDR by a different route; avif, webp and png cannot), so pair it with -t jpg. It is also skipped alongside --clarity or --remove-bg, which change the base the gain map is a ratio to. The CLI reads the X-Mochify-HDR response header and tells you when the output ended up with no gain map.

# Keep the headroom an iPhone photo already captured, converting to JPEG

mochify IMG_1234.heic -t jpg --hdr

Give an SDR photo a gain map

mochify photo.jpg --hdr generate

Or just say so

mochify photo.jpg -p "make this HDR"

Output file naming

By default, when the output format and directory match the input, the result is saved as {name}_mochified.{ext} so it's always clear something happened. If that file already exists, a numeric suffix is added (_1, _2, etc.). When the format changes (e.g. .jpg → .webp), the extension change is already unambiguous so no suffix is added.

Use -n, --name to set an explicit base name: mochify photo.jpg -t webp -n hero saves hero.webp. The prompt path also supports this: mochify *.jpg -p "optimise for Shopify, name them product" will produce product.webp, product_1.webp, etc.

PDF processing

PDFs are detected automatically by the .pdf extension, and --op picks what to do with them. (PDFs and images can't be mixed in a single command — run them separately.)

create is the exception: its inputs are images, so there is nothing in a .jpg to route on. Pass --op create, or just say "pdf" in a prompt — mochify *.jpg -p "convert to pdf" builds one too.

OpTakesReturnsWhat it does
optimizea PDF.pdfRecompresses the images inside the PDF. Text, fonts, vector art and layout are untouched, so the document stays searchable.
extracta PDF.zipPulls out the images somebody placed into the document, at the resolution they were stored at.
rasterizea PDF.zipRenders every page to an image, text and all.
splita PDF.zipExplodes the PDF into one single-page PDF per page.
createimages.pdfBuilds a PDF from images, one page per image, in the order given.
FlagApplies toDescription
--op alloptimize, extract, rasterize, split, create
-t, --type rasterize, extractpng, jpg, webp, avif, jxl — plus original for extract (no re-encode)
--dpi rasterize, optimize, createRender resolution (rasterize, default 150), target resolution for the images kept inside the PDF (optimize), or page sizing (create)
-q, --quality all but splitOutput quality 1–100 (same flag as for images)
--max-width extract, optimize, createCap image width in pixels; 0 leaves sizes alone
--min-size extract, optimizeSkip images smaller than this on either axis; 0 takes everything

| --page | create | fit (default), a4, `let

只显示了开头部分;其余内容请在仓库中阅读

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