Trendzeist – Google Trends for content ideation

Name: Trendzeist – Google Trends for content ideation
Author: phalkmin

by phalkminversion 0.2.1i★ –iRuns on your computer

Registry nameio.github.phalkmin/trendzeist-mcp

Install

Overview

Description from the maker (original English)

Free Google Trends MCP: ranked breakout/rising/evergreen topics for content ideas. No API key.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiEarly↓ 1.1K/wk · ★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Marketing & social media
You need to fill in: TRENDZEIST_PROXIES

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: TRENDZEIST_HL, TRENDZEIST_MIN_INTERVAL, TRENDZEIST_PROXIES

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "trendzeist": {
      "command": "uvx",
      "args": [
        "trendzeist-mcp"
      ],
      "env": {
        "TRENDZEIST_HL": "your-value",
        "TRENDZEIST_MIN_INTERVAL": "your-value",
        "TRENDZEIST_PROXIES": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add trendzeist --env TRENDZEIST_HL=your-value --env TRENDZEIST_MIN_INTERVAL=your-value --env TRENDZEIST_PROXIES=your-value -- uvx trendzeist-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "trendzeist": {
      "command": "uvx",
      "args": [
        "trendzeist-mcp"
      ],
      "env": {
        "TRENDZEIST_HL": "your-value",
        "TRENDZEIST_MIN_INTERVAL": "your-value",
        "TRENDZEIST_PROXIES": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "trendzeist": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "trendzeist-mcp"
      ],
      "env": {
        "TRENDZEIST_HL": "your-value",
        "TRENDZEIST_MIN_INTERVAL": "your-value",
        "TRENDZEIST_PROXIES": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

TRENDZEIST_HL env
Google Trends UI language, e.g. en-US or pt-BR.
TRENDZEIST_MIN_INTERVAL env
Minimum seconds between requests to Google (rate-limit protection).
TRENDZEIST_PROXIES secret env
Optional comma-separated proxy URLs for rotation.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account phalkmin, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Marketing & social mediai

More stars than 0% of the other 3603 servers in this category
Published to the registry more recently than 32% of the other 3603 servers in this category
Basic checks equal to or better than 100% of the other 3603 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Trendzeist – Google Trends for content ideation safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: TRENDZEIST_PROXIES

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.1) reached the registry 2 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: MCP YouTube Transcript, Google Analytics MCP, BibiGPT YouTube Video Summarizer

Alternatives

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

trendzeist-mcp

Turn Google Trends into your next 10 blog posts — in one call.

trendzeist-mcp gives your AI assistant ranked breakout / rising / evergreen topics, the questions people actually ask, an AEO opportunity finder that scores question clusters with trend, news coverage, Wikipedia presence and citability hints, plus interest curves, regional demand, real-time trends, who covers a topic in Google News and Wikipedia attention. Free, local, private. No API key, no account, no browser.

*SEO and AEO:* find the questions people ask — and answer engines answer — then make your site the source they cite. Measuring your own visibility inside ChatGPT / Perplexity / AI Overviews is out of scope; this server tells you *what to write*, not *who cites you*.

You:   Give me blog post ideas about home espresso for US readers.

Agent: → discover_topics(["espresso", "espresso machine"], geo="US") ← 1 breakout, 14 rising, 14 evergreen candidates with growth %, angles and 6 questions → mine_questions("espresso machine", geo="US") ← 30 long-tail questions: how-to 18, comparison 6, definition 4, listicle 2 → compare_keywords(["how to descale espresso machine", "best coffee beans for espresso"]) ← "Interest in 'how to descale espresso machine' rose 120% ... peaking 2026-08-30 (rising)." "1. How to Descale Your Espresso Machine (how-to, rising +120%, publish now) ..."

Built with

trendzeist-mcp is a thin MCP layer over [pytrends-modern](https://github.com/yiromo/pytrends-modern), which handles all Google Trends requests. Trendzeist adds the MCP tools and prompt, request throttling, a persistent disk cache, strict input validation, LLM-friendly JSON output and the ranked discover_topics workflow. Other runtime dependencies: mcp (official MCP Python SDK), pandas, platformdirs and requests. All MIT/BSD/Apache licensed. Google Autocomplete, Google News RSS and the Wikimedia REST API are called directly with requests (keyless).

Quick start

# any one of these

uvx trendzeist-mcp pipx run trendzeist-mcp pip install trendzeist-mcp && trendzeist-mcp docker run -i --rm ghcr.io/phalkmin/trendzeist-mcp

Claude Desktop — add under mcpServers in claude_desktop_config.json (macOS ~/Library/Application Support/Claude/, Windows %APPDATA%\Claude\, Linux ~/.config/Claude/):

"trendzeist": { "command": "uvx", "args": ["trendzeist-mcp"] }

Claude Code: claude mcp add trendzeist -- uvx trendzeist-mcp Cursor / VS Code / Codex: same command/args shape — see llms-install.md (written so you can paste it to an AI assistant and let it do the install).

Tools

Tool	What you get
`discover_topics`	Ranked blog topics from 1-5 seeds: breakout > rising > evergreen, deduped, each with a title `angle` and an explainable `score`; plus `questions[]` people ask, `suspect[]` spam-like rising queries and `filtered_out[]` rising queries unrelated to the seeds, both kept out of the ranking. Pass `site_queries` (what your site already ranks for) to mark each topic `covered / partial / gap`; seeds that name several entities get `ambiguous` + `clarify` (ask before writing)
`mine_questions`	Long-tail questions about a seed from Google Autocomplete (`how to`, `why`, `what is`, `vs` …, localised for pt / es / fr / de / it / pl / nl when `geo` or `TRENDZEIST_HL` says so — `prefix_language` tells which), deduped, angle-tagged and ranked by a realness `score`; bare prefix + seed padding goes to `filtered_out[]` — FAQ / AEO fuel
`aeo_opportunities`	Question clusters per seed × angle, scored with the seed's recent trend (`direction_now`, `growth_3m` over 12 months), Google News coverage (publishers to quote / pitch), Wikipedia presence, your site's coverage (`site_queries`) and citability hints — one call, partial failures per source; seeds that name several entities get `ambiguous` + `clarify` (ask before writing)
`what_changed`	What moved since your last snapshot (1-90 days): new and promoted breakouts (investigate now), new rising (consider), cooled / dropped queries (refresh existing post, or review — verify with `interest_over_time` before retiring), rank moves and a `direction_now` flip — from the local observation archive. First run: `first_seen[]` (current state, no history yet); no snapshot old enough: compares with the oldest and says its real age
`seasonality`	When demand peaks each year (5-year weekly data): `peak_months`, `seasonal_strength`, `next_peak`, `publish_by` (6 weeks before), one-sentence `insight`
`compare_channels`	Where a topic grows: web / YouTube / News / Images / Shopping with `growth_3m`, `direction_now`, `fastest_channel`, `momentum` (growing / flat / all_declining) and a `format_hint` (video tutorial, buying guide, newsjacking piece …)
`trend_history`	Everything the local archive has seen about a keyword: `first_seen`, `breakout_episodes` (separate runs; recurring = durable page) vs `breakout_observations` (polling count), `direction_timeline` per timeframe, `seen_under_seeds` — free, no requests
`recurring_topics`	Topics that keep breaking out in the local archive (≥ `min_episodes` separate runs in `days`, runs that overlap or restart within 7 days, under any seed, count once): `episodes`, first/last breakout, seeds, and the action one durable page, refreshed at each spike — free, no requests
`news_coverage`	Who covers a topic in Google News: headlines, publisher frequency table, recency histogram, coverage label
`wiki_attention`	Exact-title Wikipedia article and daily pageviews (direction, growth); `has_article=false` and optional `related_article` when only a different search hit is found
`trendzeist_status`	Health of every source (live / error / idle), cache usage, observation archive (rows, dates, last error), effective settings — free, no requests
`interest_over_time`	0-100 interest curve with mean, peak, `direction` (whole window), `direction_now` (recent slope), `growth_3m` / `growth_12m` and a plain-English `insight`
`compare_keywords`	Head-to-head share for 2-5 keywords, each with a `role` (leader, rising challenger, declining, niche, steady) and a `content_implication`; `winner` = the term to target (a rising challenger beats a falling leader; `null` + `winner_reason` when nothing has measurable interest) plus a one-line `seo_interpretation`
`related_queries`	Top & rising related searches with breakout flags, angles and `questions[]`
`related_topics`	Top & rising Knowledge-Graph topics (best-effort)
`interest_by_region`	Where demand lives: COUNTRY (worldwide), REGION (within a country), CITY / DMA (US or worldwide)
`suggest_keywords`	Disambiguate a term into Google entities (title, type, mid)
`trending_now`	What's trending right now, with news headlines; `topic_filter` keeps only trends mentioning your words
`list_categories`	Find Google Trends category ids to narrow any query

Prompts: blog_ideas_from_trends(topic, audience, geo) (guided ideation), content_brief(topic, audience, geo) (titles, outline, FAQ, regions, publishers), answer_brief(question, geo) (a citable answer: direct answer, statistic, quote, sources, FAQ, schema) and weekly_review(seeds, geo, site_queries) (content meeting: publish now / plan for a date / refresh / retire). A ready-made agent skill lives in SKILL.md.

Output conventions

Every result carries schema_version (currently 3; bumped only when a field is removed or changes meaning) and _meta with requests_made, cache_hit, cache_hits, cache_misses for that call — so the model knows when to slow down. _meta.archive_error appears only when the local archive could not be written (the tool result is unaffected).
Explainable score. discover_topics.topics[] and aeo_opportunities.opportunities[] carry score (0-100) and score_breakdown with five components, each {points, max, reason}: demand 25 (questions found or top-query popularity), momentum 25 (direction_now + breakout / rising), freshness 15 (Google News, 0 when not fetched), gap 20 (vs. site_queries: gap 20 / partial 10 / covered 0; neutral 10 without them), aeo 15 (question-shaped; definition angle with no Wikipedia article). Compare scores within one call only.
Observation archive. Every fresh fetch (not cache hits) of related queries, trend labels, trending searches and mined questions becomes one snapshot (unique id; an empty Google answer is a snapshot too) with normalised rows in archive.sqlite3 next to the disk cache (stdlib sqlite3, 365-day retention, opened lazily). Related-query snapshots hold the *complete* lists regardless of a caller's limit, so comparisons never invent drops. what_changed, trend_history and recurring_topics read it; trendzeist_status.archive reports it. Suspect rising queries never enter it. Archive errors never fail a tool. TRENDZEIST_ARCHIVE=0 turns it off.
Site coverage is conservative but not literal. An aeo_opportunities cluster is covered only when *every* question in it is covered; a mix is partial (see coverage_counts), so exclude_covered can never hide an unanswered question. Tokens are compared after plural folding and a small tech synonym map (mac/macos, wp/wordpress, js/javascript …), so "claude code mac" is covered by a site query "claude code macos"; matched names the site query behind each verdict. Prefixes only match on 6-letter stems ("code" is not "codex"), and a one-word head term inside a longer site query ("claude" in "claude code macos") is partial, not covered. Feeding the raw Search Console variants still helps.
angle is one of how-to | comparison | listicle | definition | verdict | news (or null) — the title format the query suggests. Pair it with evidence: how-to → steps + numbers, comparison → table + quotes, definition → cite a primary source, verdict (yes/no questions: "is it worth it", "does it work") → the verdict first, the deciding evidence, then caveats, news → dated publisher quotes.
Anything silently adjusted is reported: clamped limits add a note, empty results add a reason.
Two trend labels. direction compares the first and last third of the window (rising | falling | stable | new | no_interest | insufficient_data; new = no interest in the first third). direction_now compares the last quarter of the window with the quarter before it and answers "is it still growing *now*?". A topic that peaked mid-window reads direction: rising (or new) and direction_now: falling; the insight sentence says so. Composites (discover_topics, aeo_opportunities) always fetch the seed trend on today 12-m (echoed as query.trend_timeframe) and score on direction_now.
Suspect rising queries. Search-manipulation campaigns attach one name to many unrelated "Breakout" queries. related_queries flags such items suspect: true with a suspect_reason (a flagged .com also flags the queries carrying its name as words); discover_topics moves them to suspect[]; aeo_opportunities ignores them. Google's is_breakout value is kept, only the trust changes.
Off-topic related queries. Under niche seeds Google lists unrelated searches ("how to bake a cake" under an AI-tool seed) as breakouts from a tiny base and at values 0-3 in the top list. A breakout, or a top query below 10, that shares no word with the seed, the call's other seeds or the seed's on-topic top queries is off_topic: true (exact words after plural folding; generic words like make, work, best, github don't count). discover_topics mov

Only the beginning is shown; read the rest in the repo

Trendzeist – Google Trends for content ideation

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Marketing & social mediai

Common questions

Alternatives

MCP YouTube Transcript

Google Analytics MCP

BibiGPT YouTube Video Summarizer

README from the maker

trendzeist-mcp

Built with

Quick start

Tools