Store owners pick products from supplier catalogs and hope demand shows up. Trends MCP lets an AI assistant read Amazon search interest, Google Shopping intent, TikTok hashtag momentum, and Google Search curiosity in one place so new collections and ad hooks track what shoppers are already moving toward.
Admin dashboards explain orders, sessions, and conversion. They rarely explain whether a product class is heating up across Amazon, short video, or shopping comparison before the store sees a click. Trends MCP gives an AI assistant structured time series and growth metrics from multiple commerce and discovery sources so merchandising decisions sit on the same evidence stack as ad copy and email planning.
After adding the hosted MCP server and key from trendsmcp.ai, operators ask the model to compare phrases, chart last year's seasonality, or pull ranked movers in a category. The four tools cover history (get_trends), momentum (get_growth), leaderboards (get_ranked_trends), and live lists (get_top_trends). Normalized scores make it practical to mention TikTok and Amazon in one answer without hand-merging spreadsheets.
Brands with tight inventory should weight Amazon and Google Shopping growth before committing purchase orders. Stores that rely on organic short video should stress TikTok alongside YouTube or Google Search to see whether demand starts in discovery or search. Generalists can mirror the pattern described on the e-commerce product research page: four sources in one growth call, then let the AI summarize tradeoffs.
When a keyword accelerates on Google Search but lags on Amazon, the merchant might emphasize educational content first. When Amazon and Shopping rise together, the store can push checkout-focused landing pages and catalog expansion. The assistant can draft those implications because the numbers arrive in the same thread as brand voice guidelines.
Grab a free API key, paste the MCP JSON into the AI client, and cite explicit tool names in prompts so the model invokes get_growth or get_trends instead of guessing. Technical details for JSON bodies appear in the MCP and API reference.
Tools for this workflow
get_trendsReview multi-year weekly curves for a product phrase to separate fad spikes from durable interest.
get_trends(keyword='pickleball paddle', source='amazon', data_mode='weekly')
get_growthRank collection candidates by 3M and 12M growth across Amazon, Google Shopping, TikTok, and Google Search.
get_growth(keyword='pickleball paddle', source='amazon, google shopping, tiktok, google search', percent_growth=['3M', '12M'])
get_ranked_trendsDiscover fast-rising product-related queries to name collections, metafields, or ad keywords.
get_ranked_trends(source='google shopping', sort='mom_pct_change', limit=40)
get_top_trendsCapture what is trending on commerce or social feeds during a launch week for timely merchandising.
get_top_trends(type='Amazon Best Sellers Top Rated', limit=25)
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