# GlanceAI Fashion MCP

> Use this tool when you need to enhance customer shopping experiences through virtual try-on and personalized product recommendations. The GlanceAI Fashion MCP solves problems of product discovery and fitting uncertainties, providing an interactive interface for users to upload images or select products from the Glance catalog and receive virtual try-on outputs. It is ideal for e-commerce and retail applications where immersive shopping experiences can drive engagement and sales.

Canonical page: https://skillsregistry.net/skills/com-glance-glanceai-fashion  
JSON: https://api.skillsregistry.net/v1/skills/com-glance-glanceai-fashion

## Description

Fashion product discovery and virtual try-on via the Glance catalog

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-06-16

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/com.glance%2Fglanceai-fashion)

## Use it

MCP endpoint published by the skill: `https://glance.com/mcp`

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": "com-glance-glanceai-fashion"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/com-glance-glanceai-fashion` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/com-glance-glanceai-fashion/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