# GlanceAI Fashion MCP

> Use this tool when you need to enhance customer shopping experiences with virtual try-on and personalized product recommendations. It solves problems of inaccurate size predictions and style matching by providing immersive and interactive product discovery. The GlanceAI Fashion MCP takes in user preferences and outputs curated fashion product suggestions with virtual try-on capabilities.

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

## 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%2Fjanus)

## 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-janus"
    }
  }
}
```

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

---
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