MCP Servers

Sephora MCP Server

Enables users to search for beauty products, manage shopping baskets, and complete purchases on Sephora via an AI assistant. It also provides functionality to check Beauty Insider reward points and tier status using browser automation.

README

@striderlabs/mcp-sephora

MCP connector for Sephora beauty retail. Search products, manage your basket, complete purchases, and check Beauty Insider rewards — all from an AI assistant.

Tools

Tool	Description
`sephora_search_products`	Search for beauty products by keyword, category, and sort order
`sephora_get_product`	Get full product details, variants (shades/sizes), and reviews
`sephora_add_to_basket`	Add a product to the shopping basket
`sephora_view_basket`	View basket contents, quantities, and totals
`sephora_checkout`	Complete purchase with shipping and payment details
`sephora_get_rewards`	View Beauty Insider points, tier, and available rewards

Setup

# Install Playwright browser (one-time)
npx playwright install chromium

# Run the MCP server
npx @striderlabs/mcp-sephora

MCP Configuration

Add to your MCP client configuration:

{
  "mcpServers": {
    "sephora": {
      "command": "npx",
      "args": ["@striderlabs/mcp-sephora"]
    }
  }
}

Usage Examples

Search for products

sephora_search_products({ query: "vitamin C serum", category: "skincare", max_results: 5 })

Get product details

sephora_get_product({ product_url: "https://www.sephora.com/product/...", include_reviews: true })

Add to basket

sephora_add_to_basket({ product_url: "https://www.sephora.com/product/...", quantity: 1 })

Checkout (dry run)

sephora_checkout({ email: "...", first_name: "...", ..., dry_run: true })

View rewards

sephora_get_rewards({ email: "you@email.com", password: "yourpassword" })

Technical Details

TypeScript with strict mode
Playwright headless Chromium for browser automation
Session management — single shared browser context with 30-minute timeout
MCP SDK @modelcontextprotocol/sdk over stdio transport

Author

Strider Labs <hello@striderlabs.ai>

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