Lumnix
io.github.moltstudios/lumnix
E-commerce research via MCP. Amazon, Alibaba & AliExpress product search and FBA margins.
This endpoint completed initialize and tools/list. No tool was called.
- Rank
- #2001
- Score
- 82
- Tool tokens
- 622
- Tools
- 19
Tools
Token cost is the o200k count of the tools list JSON, including schemas, before any tool is called. Showing 12 of 19.
amazon_search_products
Search Amazon for products with filters. Returns titles, prices, ratings, ASINs, images.
amazon_get_product_details
Get detailed product information by ASIN. Returns title, price, ratings, reviews count, dimensions, weight, images, seller info, and Keepa data.
amazon_estimate_sales
Estimate monthly sales and revenue for a product based on BSR, reviews, and market data.
amazon_opportunity_score
Calculate opportunity score (0-100) for a product niche. Analyzes demand, competition, margins, and market trends. Higher = better opportunity.
amazon_analyze_competition
Analyze competition level for a keyword. Returns seller count, average price, review counts, and market saturation.
amazon_best_sellers
Get best-selling products by category with sales estimates, BSR, pricing, and trend data.
amazon_keyword_suggestions
Get keyword suggestions for Amazon. Returns related keywords with estimated search volume and competition.
amazon_price_history
Get price history for a product using Keepa data. Returns price over time, deal detection, and price statistics.
amazon_bsr_history
Get BSR (Best Sellers Rank) history using Keepa data. Track ranking trends and seasonal patterns.
amazon_analyze_negative_reviews
Analyze negative reviews for a product. Extracts common complaints, defect patterns, and improvement opportunities.
amazon_analyze_listing_quality
Score listing quality (0-100) for click-through rate and conversion rate. Checks title, bullets, images, A+ content.
alibaba_search_products
Search Alibaba for suppliers and products. Returns product details, MOQs, prices, and supplier ratings.
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