genpark-ecommerce-copilot-skill
AI-powered catalog enrichment agent designed for cross-border e-commerce visual assets generation and listing optimization.
Install / Use
claude mcp add alphaparkinc -- npx -y github:alphaparkinc/genpark-ecommerce-copilot-skillIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AutomationSupported Platforms
Skill content
View source on GitHubgenpark-ecommerce-copilot-skill
GenPark AI Agent Skill -- # E-Commerce Visuals & Catalog Enrichment Copilot Skill
This repository contains the E-Commerce Visuals & Catalog Enrichment Copilot Skill — a modular developer Python client SDK wrapper, agent skill definition, and runnable example workflows designed to automate the generation of high-quality product images, model try-on visual changes, background scene adjustments, and localized catalog SEO copywriting translation.
🚀 Capabilities
- AI Visual Modeling Tasks: Automatically apply models onto clothing items, switch background scenes for lifestyle branding, remove backgrounds, or scale image resolution.
- Localized Catalog Translations: Translate listing content (Title, Bullet Points, Descriptions) into target regional languages while dynamically restructuring layout details according to local SEO guidelines.
- Agent Integration Interface: Expose structured inputs and outputs (
skill.json) that allow other AI agents to execute product catalog enrichment autonomously.
🛠️ Setup & Installation
-
Install dependencies:
pip install -r requirements.txt -
Configuration: Set your API environment variables if executing requests against the live production server (otherwise, client executes in mock mode):
- PowerShell:
$env:ECOM_COPILOT_API_KEY="your_api_key" - bash:
export ECOM_COPILOT_API_KEY="your_api_key"
- PowerShell:
💻 SDK Usage Reference
from ecommerce_copilot import EcommerceCopilotClient
# Initialize Client (runs in mock mode without API key)
client = EcommerceCopilotClient(api_key="your_api_key")
# Perform Model Try-on visual replacement
visual_resp = client.generate_visual_task(
image_url="https://images.example.com/sweater.jpg",
task="model_tryon",
demographic="US Gen-Z"
)
print(visual_resp["output_image"])
# Perform local listing rewrite & translation
optimized = client.optimize_listing(
title="Minimalist Merino Wool Sweater",
bullets=["100% fine merino wool", "Thermal regulation warmth"],
description="Beautiful wool sweater.",
target_languages=["ja", "de"]
)
📜 License
This project is licensed under the MIT License.
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