A free, local Google Trends MCP for AI-assisted SEO, content research, AEO, and GEO.
Content research and ideation, the way I used to do it, took a lot of time. Check Google Search Console results for a period; consult Google Analytics for better insights into interests; and then look up Google Trends for related searches or missing opportunities. All of that resulted in a spreadsheet I sent to the client with my considerations.
Today, AI can do most of the hard work, but you still need to serve the reports so it can analyze. So... what if I could use some MCPs instead, cutting some unnecessary effort?
Finding 100% free, up-to-date, open-source solutions for GA and GSC was fairly easy, but finding a good one for Google Trends was a challenge: At the time, I couldn't find a Google Trends MCP that fit what I wanted: free, open-source, local, and useful for an AI-driven content workflow.
I planned to use it on my site or for some clients, and I have a philosophy of always using a free and open-source solution unless there's no clear alternative. Well, if there are no alternatives, I can just create one, right?
Initially, it was just an MCP layer over pytrends-modern, but with a cool catch: An LLM doesn't need another JSON dump; instead, it needs the data organized around the question it's trying to answer. So, my MCP doesn't just return the results and suggestions; it analyzes everything in the context of what I asked for.
Trendzeist adds the MCP tools and prompt, request throttling, a persistent disk cache, strict input validation, LLM-friendly JSON output, and the ranked discovertopics workflow.
Now, instead of well-formatted guesses, I can have better results for new topics and blog post ideas.
Before 0.1.0 went up, I noticed that this could be a public solution, open for anyone who wanted to use it and contribute. Obviously, it needed a cool name, right? So I brainstormed with Google Gemini until it landed on trendzeist: zeitgeist, spirit of the times, and a nod to the Year-End Google Zeitgeist reports that Google published from 2001 until it renamed them Year in Search.
The list comes back already sorted. Brand new spikes come first because they're the signals most worth investigating now. Then steadily rising topics, followed by evergreen candidates for the backlog.
Every topic comes with a suggested format (how-to, comparison, listicle) and the actual questions people type about it. That's your FAQ section, written by your own readers before you even start.
And every trend comes with a plain-English sentence explaining what happened, when it peaked, and where it's heading. The model reads the conclusion instead of doing math on a relative index and inventing one.
Remember that spreadsheet from the beginning? With the three MCPs connected, it turns into one conversation:
Pull my Search Console queries for the last 90 days, find pages ranking between positions 8 and 20, and use Trendzeist to check which of those topics are rising.
What comes back is the list I used to build by hand. On one side, posts worth refreshing because demand is climbing and I'm almost on page one. On the other, rising topics the site doesn't cover yet. Add GA to the same conversation, and you know which of those pages people actually stay on.
Once Trends, GSC, and GA are available to the same agent, you're no longer limited to keyword research. You can start asking questions about topical authority and generative search visibility.
Run it on Claude Desktop or any other app that accepts MCP, and done. Of course, for the full power of Trendzeist, you'll also need to connect GA and GSC MCPs, at least for now.
More and more people ask ChatGPT, Gemini, or Perplexity instead of Google, and those answers cite a handful of sources. aeoopportunities exists to answer one question: which topics could my site become one of those sources for?