Founders often search for Amazon demand signals, TikTok proof, and Google Shopping intent without standing up five vendor contracts. Trends MCP returns those checks as JSON through the same MCP tools a copywriter or engineer already enabled.
Direct-to-consumer teams rarely have a full-time insights desk on week one. Someone still has to validate whether a spike on TikTok matches Amazon language shoppers actually use, and whether Google Shopping interest lags or leads the social curve. Copying charts into Notion works once. It falls apart when the catalog grows.
Trends MCP standardizes those pulls behind Model Context Protocol tools so Claude, Cursor, Windsurf, or VS Code can request get_trends, get_growth, and get_top_trends with the exact source and type strings listed in https://trendsmcp.ai/llms.txt. The same contract maps to POST requests for founders who already run Make, n8n, or GitHub Actions.
Answer-first: run get_growth on the hero SKU phrase for amazon, google shopping, and google search with 30D, 3M, and 12M windows, then open tiktok only if social proof is part of the thesis.
Elaboration: divergent curves are information. If amazon rises while google search is flat, people may be buying without blogging about it, which is common in consumables. If tiktok spikes while amazon is flat, the founder should check listing copy, price, or stock before assuming demand is false. The assistant can tabulate the growth table; the founder still decides.
Answer-first: call get_top_trends on Amazon Best Sellers by Category with the relevant category string when the factory asks what finishes buyers reward this quarter.
Elaboration: static PDFs from brokers go stale. A ranked list returned as JSON slots straight into a memo the assistant drafts. Mention the timestamp field returned with live feeds so everyone knows the snapshot age. For omnichannel launches, add App Store Top Free or Google Play pulls when the product has a mobile companion.
Answer-first: Shopify surfaces catalog, cart, and store performance for merchants on Shopify, while Trends MCP reads external demand and attention signals that explain why traffic moved.
Elaboration: founders on Shopify should still connect internal analytics first. Trends MCP answers the adjacent question: is the category itself heating up off-site? Pair this page with https://trendsmcp.ai/shopify-trend-research for a workflow that bridges store metrics and public demand.
Answer-first: send POST bodies to https://api.trendsmcp.ai/api with Authorization: Bearer and the same fields the MCP tools use, then store responses in BigQuery or Airtable for weekly reviews.
Elaboration: the REST surface supports data_mode for daily versus weekly pulls on Google sources when the product needs finer grain. Never embed the API key in browser bundles. Rotate keys if a laptop was shared during a demo.
Amazon-heavy operators should read https://trendsmcp.ai/amazon-fba-trend-research. Dropship experiments belong with https://trendsmcp.ai/dropshipping-trend-research. Broader ecommerce playbooks sit at https://trendsmcp.ai/ecommerce-product-research.
Tools for this workflow
get_trendsPlot amazon search interest for a SKU phrase across seasons before locking packaging quantities.
get_trends(keyword='stanley tumbler', source='amazon')get_growthCompare YTD and 12M growth for a category phrase on google shopping against google search to see purchase intent versus research volume.
get_growth(keyword='electrolyte powder', source='google shopping', percent_growth=['YTD', '12M'])get_top_trendsPull Amazon Best Sellers by Category with the Electronics filter when the roadmap needs proof of what shoppers reward today.
get_top_trends(type='Amazon Best Sellers by Category', limit=25)FAQ