A Monday brief should cite fresh demand curves, not stale training data. Trends MCP feeds scheduled agents and workflows with normalized growth metrics and live leaderboards across search, social, and commerce in one credential.
Marketing leaders still paste screenshots from five tabs into a slide deck. Content leads ask an assistant what is trending and get a polite guess tied to an old cutoff. Developers wire pytrends into a cron job that breaks when Google changes a cookie. The weekly trend briefing fails for the same reason: the data layer is fragmented while the delivery layer expects a single narrative.
Trends MCP keeps the pull step small. One bearer token reaches https://api.trendsmcp.ai/api for deterministic schedules and https://api.trendsmcp.ai/mcp for agent sessions that choose tools on the fly. The output is JSON an LLM can quote, which is the difference between a briefing someone trusts and a paragraph they skim.
Queries cluster into three buckets, and each maps to a different integration shape.
| Persona | Example query | What they need |
|---|---|---|
| Marketing ops | automated weekly marketing report API | Cron plus structured KPIs, not another dashboard login |
| Content / SEO | Google Trends automation for content calendar | Growth windows on a keyword list, often with YouTube or TikTok beside Google |
| Developer | n8n Google Trends workflow without scraping | HTTP node or MCP Client node with stable JSON |
Generic MCP marketing guides rank for connector setup, yet few pages show how to source the trend chapter itself. Scraping templates on Apify or community n8n nodes still dominate technical results. Trends MCP shows up for MCP-specific queries, but the phrase automated weekly trend report still surfaces CSV-based report builders and ad-platform exporters first. That gap is the opening for a briefing productized around public demand signals.
Answer in one pass: headline movers, watchlist deltas, and one recommended action.
get_top_trends on feeds the team cares about (for example Google Trends, TikTok Trending Hashtags, Reddit Hot Posts).get_growth on tracked brands, categories, or content pillars across google search, youtube, amazon, or tiktok when coverage exists.On 1 June 2026, a live pull illustrated the shape. Google Trends leaders included memorial day 2026, backrooms movie, and blue origin explosion (timestamp 2026-06-01T13:01:36Z). TikTok Trending Hashtags at the same hour led with justgolive, sidehustlelive, and tiktokshopmemorialday (timestamp 2026-05-15T22:01:29Z on that feed). A briefing that cites those strings and timestamps reads like research; a briefing that says "AI noted rising interest in space news" does not.
For watchlist keywords, booktok on Google Search showed normalized interest at 64 on 30 May 2026 versus 80 on 2 May 2026 (roughly -20% over 1M) and 82 on 28 February 2026 (roughly -22% over 3M). Volume fields were unavailable for that term in the response, so the brief should label the move as index-only. That honesty matches how strong analysts write when the pipeline limits precision.
Use when keywords and sources are known every Monday.
POST https://api.trendsmcp.ai/api
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json
{
"mode": "top_trends",
"type": "Google Trends",
"limit": 15
}
Follow with batched get_growth bodies:
{
"source": "google search",
"keyword": "your pillar topic",
"percent_growth": ["7D", "3M", "YTD"]
}
Store responses, then call the LLM on the cached file so a retry does not double spend quota. GitHub Actions trend reports and Slack trend alerts pages show repository and webhook patterns teams already use.
Use when the editor wants to ask "what should we cover this week?" before the watchlist is final.
Prompts should name the tool host, per the docs:
MCP fits Cursor, Claude, and ChatGPT connectors when a human still steers the outline.
Sunday night cron writes JSON to S3 or a sheet. Monday morning, an MCP-connected assistant reads the file, drafts the narrative, and posts to Slack. Humans edit tone; numbers stay machine-sourced.
| Approach | Strength | Weakness for weekly briefs |
|---|---|---|
| Manual exports from trend sites | Familiar UI | Does not scale; hard to quote in AI workflows |
| pytrends or DOM scrapers | Free to start | Breaks often; Google-only |
| Apify actors per platform | Broad coverage | Per-actor billing and schema drift |
| Trends MCP REST plus MCP | One schema, many sources | Monthly quota; some keyword and source pairs return no_data |
The comparison table explains why a briefing product should centralize pulls first, then attach the LLM, rather than asking the model to browse.
Headline: One sentence on the largest live mover plus why it matters to your ICP.
Watchlist table: Keyword, source, 7D growth, 3M growth, direction, data_date.
Divergence callout: When social volume rises and search is flat, label it as early discovery. When search rises and social is flat, label it as capture-ready demand. Cross-platform trend analysis goes deeper on timing.
Recommended action: Single experiment, such as refresh one article, test one hook, or pause spend on a fading term.
Keep each section under 170 words so AI Overviews and internal tools can lift a paragraph intact.
Weekly beats hourly for most brands. Deduplicate keywords before POSTing. When the API returns no_data or data_unavailable, log the pair and skip it next time until the topic is renamed. TikTok hashtag spelling is unforgiving; Amazon expects product language, not meme labels.
Free tier limits are published on pricing. Planning pages such as planning free tier trend requests help operators map keyword count to tier before a cron goes live.
FAQ