# Fashion Recommendation System

> Use this tool when you need to enhance e-commerce user experience with personalized fashion recommendations. It analyzes fashion images using CLIP, extracting attributes like style, color, and fabric to generate tailored suggestions based on detected tags and user behavior. Ideal for online shopping platforms, it takes image uploads as input and outputs customized clothing recommendations.

Canonical page: https://skillsregistry.net/skills/attarmau-fashion-recommendation  
JSON: https://api.skillsregistry.net/v1/skills/attarmau-fashion-recommendation

## Description

FastMCP_RecSys is a clothing recommendation system that uses CLIP (Contrastive Language-Image Pretraining) to analyze and classify fashion images. Built with a FastAPI backend and React frontend, it extracts clothing attributes like style, color, and fabric from uploaded images, then generates personalized recommendations based on detected tags and user behavior. The system stores clothing items and their metadata in MongoDB, making it particularly useful for e-commerce platforms seeking to enhance user experience through AI-powered fashion recommendations.

## Trust

- **Trust score (0–1):** 0.87
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/attarmau-fashion-recommendation)
- **Repository:** <https://github.com/attarmau/styleclip>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "attarmau-fashion-recommendation"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/attarmau-fashion-recommendation` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/attarmau-fashion-recommendation/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt