What features does it offer?

Key features include outfit recommendations (get_complete_the_look), visual similarity search (get_visually_similar), style guide access (get_style_guide), and browsing product/outfit information.

How can I install it?

You can install it via npm, Docker, or by building from source. See the documentation for detailed instructions.

Can I customize the style guide?

Yes! The style guide is customizable to match your brand's aesthetic. Modify the content in `src/index.ts` to add custom categories or styling advice.

What are the main use cases?

The primary use cases are enhancing e-commerce experiences by providing personalized outfit recommendations, aiding in product discovery through visual search, and offering style guidance to customers.

What is the FindMine Shopping Stylist?

It's an MCP (Model Context Protocol) server that connects FindMine's styling API to LLMs, enabling features like outfit recommendations and visual search.

FindMine Shopping Stylist

Name: FindMine Shopping Stylist
Author: findmine

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Integrates FindMine's product styling AI with Large Language Models via the Model Context Protocol.

The FindMine Shopping Stylist is a Model Context Protocol (MCP) server designed to seamlessly integrate FindMine's AI-powered product styling and outfitting recommendations with applications like Claude. It enables users to browse product information, receive outfit recommendations, discover visually similar products, and access comprehensive style guidance, all through a simple API.

主な機能

01Provides access to product and outfit information via `product:///` and `look:///` URI schemes.

02Supports multiple installation options, including npm, Docker, and building from source.

03Includes prompts for outfit completion, styling guidance, and help with FindMine's tools.

04Offers tools for outfit recommendations (get_complete_the_look), visual similarity search (get_visually_similar), and accessing style guides (get_style_guide).

05Allows customization of the style guide to match specific brand aesthetics.

ユースケース

01Providing users with visually similar product suggestions.

02Integrating AI-driven product styling and outfitting recommendations into chat applications.

03Enhancing e-commerce platforms with personalized styling advice.