Turn a closet walkthrough video into a searchable wardrobe catalogue, with a local MCP server and agent skill
Turn a closet walkthrough video into a wardrobe your AI assistant can use: source frames, AI-generated front/back flat-lays, attributes, and optional narration, handed to any MCP client by a local server and the included wardrobe skill. Ask what goes with the navy jacket, what you said about it while you were filming, or what you have not worn since spring — against your own clothes, catalogued from one video, on your own machine.
By Will Gao. A mention is appreciated, but not required. MIT licensed; retain the copyright and license notice as required by MIT.
Open the live demo — one 5-minute-49-second phone recording beside the 34-garment catalogue built from it. Nothing to install, no API key, no clone.
The demo is not part of this repository, so cloning stays small. To run it offline, download closetscan-demo.zip from the latest release, unzip it, and open index.html. Keep the folder together; the page loads its images from catalogue/.
That catalogue was generated from the included recording using DINOv2 and the paid AI stages; reruns can produce different results. It contains 34 garments with 68 generated front/back images. Images marked as plates are generated reconstructions; source frames remain available for comparison.
One MCP server and one skill, both local. Point the server at a catalogue — one you build with the pipeline below, or the published demo's, which needs no pipeline run at all — and your assistant can answer from your own clothes:
From the project README.
Add the radar badge to your README — it shows your project was picked up by MCP Radar and links to this page:
[](https://mcp.liqiwa.com/s/wgaostudio--closetscan.html)
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