E-commerce research via MCP. Amazon, Alibaba & AliExpress product search and FBA margins.
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"io-github-moltstudios-lumnix": {
"command": "<see-readme>",
"args": []
}
}
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E-commerce research via MCP. Amazon, Alibaba & AliExpress product search and FBA margins.
No automated test available for this server. Check the GitHub README for setup instructions.
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This is the reference implementation for the mcp server
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AI-powered e-commerce research tools via MCP
Stop paying for three different SaaS dashboards. Ask your AI to find winning products, vet suppliers, and calculate margins — all in one conversation.
npm install lumnix
The old way: Subscribe to Jungle Scout for product research ($49/mo), Keepa for price history ($50/mo), some Chrome extension for Alibaba vetting ($20/mo), and a spreadsheet for margin math. Switch between tabs all day. Miss opportunities.
The Lumnix way: One API key. 19 tools. In your AI assistant. No dashboards. No Chrome extensions. No tab-hopping.
"Find me wireless earbuds under $20 with high sales volume, low reviews, and a supplier on Alibaba with MOQ under 500"
Your AI calls Lumnix. You get structured data with revenue estimates, competition analysis, and profit margins. You decide. Done.
Sign up at lumnix.dev — no credit card required. Get your key in 30 seconds.
Claude Desktop — edit ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"lumnix": {
"command": "npx",
"args": [
"mcp-remote",
"https://lumnix.dev/api/mcp",
"--header",
"Authorization: Bearer YOUR_API_KEY"
]
}
}
}
⚠️ Claude Desktop doesn't support remote MCP URLs natively. The
mcp-remotebridge (auto-installed by npx) makes it work. Requires Node.js installed.
Cursor — Settings → MCP → Add new global MCP server:
{
"mcpServers": {
"lumnix": {
"url": "https://lumnix.dev/api/mcp",
"headers": {
"Authorization": "Bearer YOUR_API_KEY"
}
}
}
}
Windsurf / Cline / any MCP client — same pattern as Cursor. URL + Bearer token header.
Restart your AI client. Then just talk naturally:
"Search Amazon for portable blenders with high sales and low reviews"
That's it. No Docker. No config files to debug.
Lumnix gives your AI 19 specialized tools across three platforms:
| Tool | What it does |
|---|---|
amazon_search_products | Search by keyword with price, rating, and review filters |
amazon_get_product_details | Full product page — features, specs, reviews, images, category |
amazon_estimate_sales | Monthly sales volume with confidence range |
amazon_opportunity_score | ⭐ 0-100 niche score — demand, competition, margin potential |
amazon_analyze_competition | Top players, review counts, price ranges for a keyword |
amazon_best_sellers | Best-selling products by category with sales data |
amazon_keyword_suggestions | Amazon autocomplete keywords with search frequency |
amazon_price_history | **� |