Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Runs on your computer
Remove AI Watermarks
Overview
Description from the maker (original English)
Identify and remove AI watermarks and provenance metadata from your own images and video.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
- UsageiEarly↓ 2.2K/wk · ★ –
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: Design, images & audio
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
- PyPIPython’s uv installed (for the uvx 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": {
"remove-ai-watermarks": {
"command": "uvx",
"args": [
"remove-ai-watermarks",
"mcp"
]
}
}
}Run this in your terminal
claude mcp add remove-ai-watermarks -- uvx remove-ai-watermarks mcpOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"remove-ai-watermarks": {
"command": "uvx",
"args": [
"remove-ai-watermarks",
"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.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"remove-ai-watermarks": {
"type": "stdio",
"command": "uvx",
"args": [
"remove-ai-watermarks",
"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 8, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account wiltodelta, 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 Design, images & audioi
- More stars than 0% of the other 2800 servers in this category
- Published to the registry more recently than 92% of the other 2800 servers in this category
- Basic checks equal to or better than 100% of the other 2800 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 Remove AI Watermarks 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 (0.54.1) reached the registry 3 days ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
What can I use instead?
In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
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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.
Remove AI Watermarks
Remove AI provenance marks from images and video you generated yourself:
- known visible labels such as the Google Gemini sparkle watermark and vendor text marks;
- invisible pixel watermarks through direct local-format disruption or diffusion regeneration;
- C2PA, EXIF, XMP, IPTC, and related AI metadata.
| Before | After |
|---|---|
uv tool install "remove-ai-watermarks[visible]" # CLI for visible marks and metadatanpx skills add wiltodelta/remove-ai-watermarks # agent skill for Claude Code, Codex, Cursor, and other agents
Video support covers provenance identification, complete visible-plus-metadata cleaning, directory batches, visible Sora, Veo, Seedance, Doubao, Dola, Hailuo AI, and Kling AI mark removal, and oracle-certified VAE regeneration for video SynthID removal.
raiw.cc runs this library as a hosted service, with the GPU
included and nothing to install. Visible mark and metadata removal at Standard
output up to 12 MP are free there; original resolution above 12 MP and invisible
watermark removal are paid.
This is a research project on AI provenance signals, for lawful use on content
you own. It is provided as is, without warranty or liability, and each user is
responsible for how they use it. It does not target stock agency previews or
other watermarks that protect third party paid content. Some jurisdictions,
including China, restrict removing AI labels or supplying tools that do. See
scope, safety, and legal notes.
Choose what you want to do
| Goal | Command | GPU |
|---|---|---|
| Find provenance signals and watermarks | identify | No |
| Classify a photograph from pixels (opt-in, not provenance) | classify | No |
| Remove known visible AI marks | visible | No |
| Erase a region you select | erase | No |
| Strip AI metadata | metadata | No |
| Identify supported video provenance | video identify | No |
| Remove visible marks and AI metadata from video | video all | No |
| Strip AI metadata from video | video metadata | No |
| Remove a registered visible AI mark from video | video visible | No |
| Process a directory of videos | video batch | Depends on mode |
| Apply the calibrated video-pixel SynthID-removal profile | video invisible | Recommended |
| Regenerate an image to disrupt invisible watermarks | invisible | Required (CUDA) |
| Run visible, invisible, and metadata removal | all | Recommended |
| Process a directory | batch | Depends on mode |
Microsoft Paint and Photos InvisMark declarations are routed automatically to pixel regeneration. The all command removes both the hidden pixel watermark and its linked C2PA manifest; metadata stripping alone removes only the manifest. A specialized Python API can inspect and disrupt the validated local Watermarker.dll payload without diffusion.
Installation modes
| Need | Install |
|---|---|
| Metadata inspection and stripping | remove-ai-watermarks |
| Photograph AI-versus-camera classification | remove-ai-watermarks[classify] |
| 10-provider source-export & model-version classification | remove-ai-watermarks[source-classify] |
| Visible detection and removal | remove-ai-watermarks[visible] |
| Visible video processing | remove-ai-watermarks[video] |
| Video SynthID removal | remove-ai-watermarks[video,diffusion] |
| Torch-free DWT-DCT detection | remove-ai-watermarks[detect] |
| Direct local Paint InvisMark disruption | remove-ai-watermarks[pixels] |
| Invisible image removal (needs CUDA) | remove-ai-watermarks[qwen-zimage] |
| Every production feature available on the active Python | remove-ai-watermarks[all] |
Lower-level and specialized extras include pixels, heif, trustmark, migan, lama, diffusion, classify-onnx, and source-classify. The installation guide documents their exact dependency composition, Python compatibility, and model requirements.
Quick start
Install the metadata-focused default CLI:
uv tool install remove-ai-watermarksInspect an image:
remove-ai-watermarks identify image.pngTo classify a photograph from pixels (AI versus camera, optional provider), install the extra and call classify. identify never starts it:
uv tool install --force "remove-ai-watermarks[classify]"remove-ai-watermarks classify image.png
Guide: photo pixel classification.
For a lightweight, abstaining 10-provider source-export and model-version signal after metadata removal (classify_source and CLI classify-source), use the separate API or CLI command. It is not a SynthID detector:
remove-ai-watermarks classify-source image.pngimport remove_ai_watermarks as raiwresult = raiw.classify_source("image.png") print(result.label, result.version_subfamily, result.reason)
Install remove-ai-watermarks[source-classify]. Guide: source-pipeline classification.
Signed provenance is the supported route for SynthID and identify reads it. There is no local SynthID pixel detector in the package. Research on a periodic lattice expert is in scripts/synthid_runtime/ and synthid-detector-research.md.
For visible watermark removal, install the pixel dependencies:
uv tool install --force "remove-ai-watermarks[visible]"Then remove a known visible mark and AI metadata:
remove-ai-watermarks visible image.png -o clean.pngStrip metadata without running visible inpainting or diffusion:
remove-ai-watermarks metadata image.png --remove -o clean.pngWithout -o this command overwrites the source in place.
Inspect or remove AI metadata from an MP4, MOV, M4V, WebM, MKV, AVI, or FLV file:
remove-ai-watermarks video metadata input.mp4 --checkremove-ai-watermarks video metadata input.mp4 --remove -o clean.mp4
The video metadata command does not transcode video or audio streams. Unlike the image command above, when -o is omitted it writes _clean and preserves the original. MP4 and MOV inspection includes the native TC260 AIGC tag in moov.udta.meta.keys/ilst, including a moov placed after the media payload, plus the QuickTime-form meta variants Doubao's iOS export writes (a bare meta box as a direct moov child, and a keyless hdlr=mdir metadata list). Keyed workflow and prompt entries in the same metadata-list structure are also detected and removed, including ComfyUI exports. MKV and WebM inspection reads the normative Segment.Tags.Tag.SimpleTag placement. AVI uses LIST/INFO/AIGC, while FLV uses script.onMetaData.AIGC. The non-ISOBMFF formats are remuxed with stream copy for removal.
Use the product-oriented video path to identify or clean a file:
uv tool install --force "remove-ai-watermarks[video]"remove-ai-watermarks video identify input.mp4 remove-ai-watermarks video all input.mp4 -o clean.mp4
video all removes a stable registered visible mark when present and always strips verified AI metadata. If neither signal is found, it still writes a same-container passthrough, so application callers get one predictable output contract. Proprietary invisible-video removal is excluded by default. --invisible opts into the lossy, oracle-certified video SynthID profile.
Process a directory with the same contract:
remove-ai-watermarks video batch ./videos --mode allRemove a supported visible video mark:
remove-ai-watermarks video visible input.mp4 -o clean.mp4remove-ai-watermarks video visible veo.mp4 --mark veo -o veo_clean.mp4 remove-ai-watermarks video visible seedance.mp4 --mark seedance -o seedance_clean.mp4 remove-ai-watermarks video visible dola.mp4 --mark dola -o dola_clean.mp4 remove-ai-watermarks video visible hailuo.mp4 --mark hailuo -o hailuo_clean.mp4 remove-ai-watermarks video visible kling.mp4 --mark kling -o kling_clean.mp4
This path scans the complete sequence before changing pixels. It accepts only a mark that repeats at a stable position across adjacent frames, then reuses the same OpenCV, MI-GAN, or LaMa fill backends as image removal. Audio is copied without re-encoding and is allowed to reach its natural end; the video stream is transcoded because its pixels change. By default, a guarded optical-flow pass motion-aligns the preceding accepted fill and blends it only when the nearby source context agrees; use --no-temporal-consistency to disable it. The encoder preserves supported 8-bit source chroma sampling, color tags, and MP4/MOV track timescale instead of relying on ffmpeg's implicit raw-BGR defaults. Variable frame intervals are preserved through a timestamped in-memory NUT bridge instead of being flattened to the average frame rate. Non-zero source start timestamps are retained together with the copied audio offset. The default --mark auto scans all providers in one decode pass and selects the first stable match in the specificity order shown below. Valid Google AI-video provenance breaks a Sora/Veo cross-match in favor of Veo when the diamond is nested in the Sora region or Veo persists through the complete clip while Sora does not. Pass an explicit mark to restrict detection to one provider. Sora covers the moving Sora 2 mascot, with or without the wordmark; mascot-only matches also require the complete two-eye shape. Veo covers both the current four-point diamond and the legacy Veo text. Seedance covers the fixed boxed AI label, Dola covers the fixed Dola AI text, Hailuo AI covers the composite MINIMAX | hailuo AI label, and Kling AI covers the bottom-right KLING AI or KlingAI label with its version suffix. A completed encode is published atomically. No output is written when no stable mark is found. HDR, PQ/HLG, and greater-than-8-bit inputs are rejected before encoding rather than silently reduced through OpenCV's 8-bit BGR boundary.
Apply the calibrated video-pixel SynthID-removal profile:
uv tool install --force "remove-ai-watermarks[video,diffusion]"remove-ai-watermarks video invisible input.mp4 -o clean.mp4
This path regenerates the complete sequence with one latent-noise field shared across time, copies complete audio, strips source metadata, and publishes the completed encode atomically. The default noise_std=0.15 profile passed both the two-carrier calibration and a complete public eight-second Veo oracle check. Google does not publish a local decoder, so a fresh provider check remains useful for unusually important files or after provider changes, but it is not a product result state. The CLI therefore describes
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