# K-Beauty

> Use this tool when you need to access specialized knowledge on Korean skincare and cosmetics, or solve problems related to product recommendations, ingredient analysis, and personalized skincare routines. It provides curated data on popular brands, ingredients, and multi-step routines, offering inputs such as skin type and concerns, and outputs including tailored product suggestions and routine guidance. Ideal for beauty enthusiasts, skincare professionals, and e-commerce applications seeking authoritative K-Beauty advice and product information.

Canonical page: https://skillsregistry.net/skills/alexai-k-beauty  
JSON: https://api.skillsregistry.net/v1/skills/alexai-k-beauty

## Description

This K-Beauty MCP server provides specialized knowledge about Korean skincare and cosmetics through curated data on popular brands, ingredients, and skincare routines. Built with Python using the MCP framework and featuring structured data modules for brands like COSRX and Laneige, ingredient information including benefits and skin type compatibility, and multi-step Korean skincare routines for different skin concerns, it offers tools for product recommendations, ingredient analysis, and personalized routine suggestions. The implementation includes comprehensive skincare data covering anti-aging, acne-prone, and basic routines with step-by-step guidance, making it valuable for beauty enthusiasts seeking Korean skincare advice, skincare professionals building recommendation systems, and e-commerce applications requiring specialized K-Beauty product knowledge.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ecommerce
- **Updated:** 2026-09-02

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/alexai-k-beauty)
- **Repository:** <https://github.com/alexai-mcp/k-beauty-mcp>

## 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": "alexai-k-beauty"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/alexai-k-beauty` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/alexai-k-beauty/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