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。
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FaintMark

作者:matchalatteguy版本 0.1.0i★ –i在你的电脑上运行
注册名称io.github.matchalatteguy/faintmark

安装

概览

作者提供的说明(英文原文)

Invisible per-recipient image watermarks. Mark one copy per recipient, then identify a leaked copy.

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

  • PyPI已安装 Python 的 uv(用于 uvx 命令)

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": {
    "faintmark": {
      "command": "uvx",
      "args": [
        "faintmark",
        "mcp"
      ]
    }
  }
}

在终端中运行这条命令

claude mcp add faintmark -- uvx faintmark 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": {
    "faintmark": {
      "command": "uvx",
      "args": [
        "faintmark",
        "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": {
    "faintmark": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "faintmark",
        "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。

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 matchalatteguy 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 2204 个服务器的 0%
  • 发布到注册中心的时间比此分类中其他 2204 个服务器的 52% 更新
  • 基础检查结果等于或优于此分类中其他 2204 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

FaintMark 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(0.1.0)于27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 Python (uv)。

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。

FaintMark

Invisible per-recipient image watermarks. Create one marked copy per recipient, then identify which copy a shared or leaked image is. Designed to tolerate the recompression and resizing chat apps apply; see the app tests and limits below. Runs locally, no account, no upload. Python CLI and MCP server.

$ faintmark mark photo.jpg alice bob

alice 991e318a21 /Users/me/Pictures/marked/photo-991e318a21.jpg bob 746ac9fa88 /Users/me/Pictures/marked/photo-746ac9fa88.jpg 2 copies in /Users/me/Pictures/marked

$ faintmark check ~/Downloads/forwarded.jpg matched: alice 991e318a21 marked 2026-10-06T23:11:54Z

Send each person only their own file; file names carry the id, not the name. A match identifies the label the copy was issued under, not who shared it. The mark is intended to be visually unobtrusive on photographs. JPEG, PNG and WebP keep their format; HEIC becomes JPEG.

Install

uvx faintmark mark photo.jpg alice bob   # runs without installing; needs uv

uv tool install faintmark # or: pipx install faintmark

Python 3.11 or newer on macOS, Linux or Windows (Intel Macs: 3.11 to 3.13). uv can install Python and run FaintMark. The first mark or check downloads Adobe's TrustMark Q models (65 MB, SHA-256 verified) into ~/.faintmark. For HEIC input install faintmark[heic]: uv tool install 'faintmark[heic]', or without a persistent install uvx --from 'faintmark[heic]' faintmark mark photo.heic alice. uv tool uninstall faintmark removes the command and leaves ~/.faintmark in place.

faintmark mark IMAGE RECIPIENT... [-o DIR] [--format png|jpeg|webp] [--json]

faintmark check IMAGE [--deep] [--files] [--json] faintmark list [-n N] [--files] [--json]

Copies go into marked/ beside the image unless -o says otherwise. Quote labels with spaces: faintmark mark photo.jpg 'Alice Smith'. One run marks 1 to 100 recipients. --json prints the result the matching MCP tool returns; mark includes the source file name and output paths, check and list omit file names and paths unless --files is set. check --deep also tries a flip and small rotations, and when nothing is detected lists up to three registered ids within 26 of 96 codeword bits of the raw decoder output as candidates, with their bit distance. Those are uncalibrated and can be coincidental or forged; they are never a match. With --json, errors print {"error": "..."}. check exits 0 for matched, 1 for unregistered or not_detected, 2 for an error.

mark accepts non-animated JPEG, PNG, WebP and HEIC up to 25 megapixels without transparency (16-bit RGB is read at 8 bits; 16-bit grayscale and CMYK are rejected) and needs about 1.5 GB of memory at that size. check reads the first frame of anything Pillow opens, up to 100 megapixels.

Agents

claude mcp add --scope user faintmark -- uvx faintmark mcp

codex mcp add faintmark -- uvx faintmark mcp gemini mcp add -s user faintmark uvx faintmark mcp

Any other client that reads an mcpServers config (Claude Desktop, Cursor, Windsurf): add this entry to the client's MCP configuration. The client must find uvx on its PATH; set FAINTMARK_HOME in the server's environment to use another registry.

{ "mcpServers": { "faintmark": { "type": "stdio", "command": "uvx", "args": ["faintmark", "mcp"] } } }

Choose one route per client; plugins and extensions bundle the skill too. For HEIC input start the server as uvx --from 'faintmark[heic]' faintmark mcp; the bundled launchers use the base package.

  • Add to Cursor
  • Add to VS Code
  • Claude Code plugin: claude plugin marketplace add matchalatteguy/FaintMark then claude plugin install faintmark@faintmark
  • Codex plugin: codex plugin marketplace add matchalatteguy/FaintMark then codex plugin add faintmark@faintmark
  • Gemini extension: gemini extensions install https://github.com/matchalatteguy/FaintMark
  • Skill for any agent with a shell: npx skills add matchalatteguy/FaintMark
ToolArgumentsReturns
mark_imageimage_path, recipients, optional output_dir, formatoutput folder and each copy's id, path, warnings
check_imageimage_path, optional files, deepstatus of matched (with recipient, id, marked_at, and same_image when a stored hash exists), unregistered (with id) or not_detected; with deep, transform naming the flip or rotation that recovered the result, and suspects (id, recipient, bit_errors, same_image) plus registry_size when nothing was detected
list_copiesoptional limit, filesregistered copies, newest first

Give tools absolute paths. unregistered means an id was decoded but it is not in this machine's registry; not_detected means no readable mark, which says nothing about where the image came from. same_image compares perceptual hashes with the issued copy: false means they differ beyond the threshold, which cropping or an id copied into another picture can cause; the comparison can also miss differences.

check_image and faintmark check --json return one of these: the three plain statuses (a match with same_image: false means the picture differs from the issued copy); with deep, a result recovered by a transform, or a miss with candidates (suspects is empty when no registered id is within the cutoff). The CLI prints errors as the last line; MCP tools raise them as tool errors (isError): messages from the service match, argument validation messages differ.

{"status": "matched", "id": "991e318a21", "recipient": "alice", "marked_at": "2026-10-06T23:11:54Z", "same_image": true}

{"status": "matched", "id": "991e318a21", "recipient": "alice", "marked_at": "2026-10-06T23:11:54Z", "same_image": false} {"status": "unregistered", "id": "3123f6f877"} {"status": "not_detected"} {"status": "matched", "id": "991e318a21", "recipient": "alice", "marked_at": "2026-10-06T23:11:54Z", "same_image": true, "transform": "rotated 4"} {"status": "not_detected", "suspects": [{"id": "991e318a21", "recipient": "alice", "bit_errors": 21, "same_image": true}], "registry_size": 100} {"error": "forwarded.jpg: no such file"}

mark_image and faintmark mark --json return the first line; list_copies and faintmark list --json return the second, newest first:

{"original": "photo.jpg", "output_dir": "/Users/me/Pictures/marked", "copies": [{"id": "991e318a21", "recipient": "alice", "path": "/Users/me/Pictures/marked/photo-991e318a21.jpg", "warnings": []}]}

{"copies": [{"id": "991e318a21", "recipient": "alice", "marked_at": "2026-10-06T23:11:54Z", "warnings": []}]}

Tested on real apps

7 October 2026, FaintMark 0.1.0, three source photos (an iPhone scene, a CC0 portrait, a CC0 sunset). Each row reports the samples actually sent on that route at default photo quality. Screenshot rows are screenshots of the receiving phone, cropped to the photo before checking. These are individual round-trip observations, not recovery rates or guarantees for an app.

RouteReceivedResult
WhatsApp photo, all threelong edge 1600 px, 155 to 317 KBmatched 3/3
Discord attachment, sceneoriginal size, 1.7 MBmatched 1/1
Discord sticker made from the scene217x285 PNGmatched 1/1
Telegram photo, scene960x1280, 102 KBmatched 1/1
WeChat photo, portrait and sunsetlong edge 1644 to 1920 px, 67 to 302 KBmatched 2/2
Instagram DM, portrait1206x804, 176 KBmatched 1/1
Chat screenshots on WhatsApp, Discord, Telegram, WeChat, Instagramphoto long edge 286 to 1022 pxmatched 9/9
Tinder profile card, portrait (screenshot)heavy cropnot detected 0/1

Every match also reported same_image: true. The originals, every received file, the screenshots, the crops and a manifest of expected ids and results (docs/evidence-2026-10-07.json) are in the evidence release. On a machine without this registry, the received files return unregistered with the id from the manifest; the originals and the Tinder crop return not_detected. X, Signal, iMessage and Instagram stories were not tested.

How it works

TrustMark Q (Adobe, MIT) embeds a 40-bit id as an image-wide pattern designed to tolerate JPEG recompression, WebP conversion and moderate resizing. This is forensic watermarking, not steganography: anyone with TrustMark can read the id; only your registry maps it to a name. FaintMark draws a random id per recipient, writes the copy in the source format (JPEG at the source's own quantization tables, PNG, WebP; HEIC becomes JPEG), decodes the saved copy to verify its id is recoverable, and records id, recipient, file and a perceptual hash of the copy in a local SQLite registry. On a registered match, check compares perceptual hashes and reports same_image: false when their distance exceeds the threshold. A JPEG whose source settings lose the mark is saved at quality 95 instead, and says so in its warnings. Marking an image that already carries a mark replaces it and says so. A preflight re-encodes each copy at JPEG quality 70, at full size (skipped with a warning when a side exceeds 65,500 px, JPEG's limit) and resized to 1280 px (half size when the image is smaller), and warns when the id does not survive; send those copies as a file rather than a photo.

ICC profiles are kept so Display P3 photos stay the same colour. EXIF and other metadata are not copied.

Compatibility with Adobe's implementation is checked in: tests/fixtures holds BCH vectors and two images marked by upstream TrustMark 0.9.2; FaintMark decodes their ids and reproduces their marked pixels within one value per RGB channel. A chat-app style ladder in the real-model tests (resize to 1600, 1280 and 1024 px with JPEG 70 to 80, WebP 75, and a chained resize-plus-JPEG pass, on delivered JPEG bytes) recovers the id on two 12-megapixel synthetic covers and the 320 px fixture, except WebP 75 on the fixture.

Attacks we measured

Someone who has this repository and a copy can do the following; measured on three photos at 2000 px, two ids each, full tables in the attack report attached to the evidence release.

  • Erase the mark invisibly. Re-running the public encoder with a random payload removes it at 42 to 47 dB PSNR (6/6). check then says not_detected, exactly as for an unmarked photo.
  • Overwrite it. Re-marking with another id wins every time (last writer wins, 41 to 44 dB). In these trials the decoder read the replacement and never the previous id.
  • Combine copies. Averaging two or three recipients' copies defeats the plain decoder every time. Against a registry of 100 ids, the closest registered codeword belonged to a colluder in 264 of 264 trials (12 to 30 bits away; the closest innocent was 28 to 41 away), and with the 26-bit cutoff check --deep lists at least one colluder in 253 of

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