Editors and SEO leads often search for ways to align pitch meetings with demand curves instead of static three-month guesses. Trends MCP lets assistants fetch Google Search history, Google News interest, Wikipedia attention, and breakout leaderboards in one session.
Calendars fail for predictable reasons: finance wants quarterly themes, product wants launches, and SEO wants clusters that do not match either set. Without a shared demand layer, the meeting becomes a negotiation instead of a ranking exercise. Assistants help only when they can cite fresh curves, not yesterday's slide deck.
Trends MCP gives editors the same primitives researchers use: get_trends for long series, get_growth for percent change windows, and get_top_trends for ranked live feeds such as Google Trends, Google News Top News, and YouTube Trending. Documentation lives at https://trendsmcp.ai/docs, and the quick routing guide is https://trendsmcp.ai/llms.txt.
Answer-first: spend the first ten minutes pulling get_growth tables for every pillar candidate on google search, then ten minutes on google news for the two pillars that depend on policy or product news, then five minutes on get_top_trends for reactive slots.
Elaboration: the remainder of the hour belongs to humans: brand voice, legal constraints, and staffing. The assistant should exit with a ranked markdown table that includes the percent change, recent_date, and baseline_date fields returned by get_growth so editors can spot volatility instead of mistaking noise for a mandate.
Answer-first: publish the shared list as a living document where each keyword row links to the last Trends MCP pull timestamp and the source string used.
Elaboration: SEO owners still validate difficulty elsewhere. Trends MCP answers whether interest is rising or fading, which prevents chasing clusters that look big but decayed last quarter. For cross-format bets, add youtube and tiktok pulls on the same phrases so video teams see divergent curves early.
Answer-first: wikipedia page views help when the calendar covers educational explainers, scientific topics, or public figures where search spikes lag article traffic.
Elaboration: wikipedia is not a social network, so spikes usually mean homework-style intent. Pair those curves with google search before rewriting a whole month around a celebrity spike that does not match customer language.
Answer-first: treat leaderboard rows as alerts, not assignments, until an editor approves the angle against guidelines.
Elaboration: reactive content wins when teams prewrite guardrails: banned topics, required disclaimers, and who can approve a fast publish. Trends MCP supplies the list; humans supply judgment. For sensitive categories, add news sentiment pulls on the entity name before drafting.
Content strategy teams should read https://trendsmcp.ai/content-strategy. Keyword owners can pair this page with https://trendsmcp.ai/seo-keyword-research. Newsletter programs gain more cadence detail at https://trendsmcp.ai/newsletter-growth-trend-research.
Tools for this workflow
get_trendsChart twelve months of google search interest for a pillar topic before assigning writers.
get_trends(keyword='heat pump tax credit', source='google search')get_growthRank ten working titles by 3M growth on google search and google news in two batched calls each.
get_growth(keyword='heat pump tax credit', source='google news', percent_growth=['3M', '12M'])get_top_trendsPull Google News Top News at the start of the Monday meeting for reactive pitches that still fit brand voice.
get_top_trends(type='Google News Top News', limit=25)FAQ