# FastMCP_RecSys

> FastMCP_RecSys — attarmau-fastmcp-recsys. Use this tool when you need to analyze clothing images and receive personalized fashion recommendations. FastMCP_RecSys solves the problem of discovering similar clothing items and providing accurate tags through visual analysis, ideal for e-commerce, fashion blogging, and virtual styling applications. It takes clothing images as input and outputs relevant tags and recommendations, streamlining the fashion discovery process.

Canonical page: https://skillsregistry.net/skills/attarmau-fastmcp-recsys  
JSON: https://api.skillsregistry.net/v1/skills/attarmau-fastmcp-recsys

## Description

A CLIP-Based Fashion Recommender system that allows users to upload clothing images and receive tags and recommendations based on visual analysis.

## Trust

- **Trust score (0–1):** 0.87
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** media
- **Updated:** 2026-09-28

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/aoxux8ydhh)
- **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-fastmcp-recsys"
    }
  }
}
```

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