Wikipedia trend data as clean JSON: page view time series for any topic, growth rates and the live most-viewed articles feed from one REST endpoint. A clean proxy for public attention.
One endpoint. One API key. One normalized 0-100 trend score you can compare against 14 other platforms.
Docs: https://trendsapi.ai/#quickstart · llms.txt: https://trendsapi.ai/llms.txt · Free API key (100 req/mo): https://trendsapi.ai/#get-key
curl -X POST https://api.trendsapi.ai/api \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"mode": "get_growth", "source": "wikipedia", "keyword": "artificial intelligence", "percent_growth": ["3M", "12M"]}'{
"keyword": "artificial intelligence",
"source": "wikipedia",
"growth": { "3M": 41.8, "12M": 212.4 },
"timestamp": "2026-08-03T12:00:00Z"
}1. Get a free API key at https://trendsapi.ai/#get-key - 100 requests/month, no credit card.
2. Make your first call:
curl -X POST https://api.trendsapi.ai/api \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"mode": "get_time_series", "source": "wikipedia", "keyword": "artificial intelligence"}'Python:
import requests
res = requests.post(
"https://api.trendsapi.ai/api",
headers={"Authorization": "Bearer YOUR_API_KEY"},
json={"mode": "get_growth", "source": "wikipedia", "keyword": "artificial intelligence",
"percent_growth": ["3M", "12M"]},
)
print(res.json())Node.js:
const res = await fetch("https://api.trendsapi.ai/api", {
method: "POST",
headers: {
Authorization: "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
},
body: JSON.stringify({ mode: "get_growth", source: "wikipedia", keyword: "artificial intelligence",
percent_growth: ["3M", "12M"] }),
});
console.log(await res.json());| Mode | What it returns | Needs a keyword? |
|---|---|---|
get_time_series |
Historical page views as a normalized 0-100 series | yes |
get_growth |
Growth % over 3M / 6M / 12M / 5Y windows | yes |
get_top_trends |
Live trending feeds (21 of them) | no |
| Wikimedia Pageviews API | Trends API | |
|---|---|---|
| Normalization | raw counts, DIY | 0-100 score, done |
| Growth rates | compute yourself | 3M/6M/12M/5Y built in |
| Trending feed | separate endpoint | included, one call |
| Cross-source compare | no | same scale as 14 other sources |
| Free tier | free (rate limited) | 100 requests/month |
- Investment research: rising page views on a company or technology as an attention signal
- PR measurement: did the press coverage actually move public attention?
- Research: track when a topic enters public consciousness
- Editorial: find what the world is looking up right now
The same API key powers the Trends API MCP server, so Claude, Cursor, VS Code, ChatGPT and any MCP-compatible client can query this data in natural language.
+ Add to Cursor (one click)
Cursor / Windsurf / Cline (~/.cursor/mcp.json or equivalent):
{
"mcpServers": {
"trendsapi": {
"url": "https://api.trendsapi.ai/mcp",
"transport": "http",
"headers": { "Authorization": "Bearer YOUR_API_KEY" }
}
}
}VS Code / GitHub Copilot (.vscode/mcp.json):
{
"servers": {
"trendsapi": {
"type": "http",
"url": "https://api.trendsapi.ai/mcp",
"headers": { "Authorization": "Bearer YOUR_API_KEY" }
}
}
}Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"trendsapi": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://api.trendsapi.ai/mcp", "--header", "Authorization:${AUTH_HEADER}"],
"env": { "AUTH_HEADER": "Bearer YOUR_API_KEY" }
}
}
}Claude.ai (browser): Settings -> Connectors -> Add custom connector -> https://api.trendsapi.ai/mcp
Then ask things like:
How did "creatine gummies" grow on TikTok vs Google over the last 12 months?
What is trending on YouTube right now?
| Source | source value |
What it measures |
|---|---|---|
| Google Search | google search |
Search volume |
| Google Images | google images |
Image search volume |
| Google News | google news |
News search volume |
| Google Shopping | google shopping |
Shopping search volume |
| YouTube | youtube |
Search volume |
| TikTok | tiktok |
Hashtag volume |
reddit |
Subreddit subscribers | |
| Amazon | amazon |
Product search volume |
| Wikipedia | wikipedia |
Page views |
| News volume | news volume |
Article mention volume |
| News sentiment | news sentiment |
Positive / negative score |
| App downloads | app downloads |
Android downloads (AppBrain) |
| App rankings | app rankings |
Android chart position |
| npm | npm |
Weekly package downloads |
| Steam | steam |
Concurrent players (monthly) |
| Feed | type value |
|---|---|
| Google Trends | Google Trends |
| Google News Top News | Google News Top News |
| TikTok Trending Hashtags | TikTok Trending Hashtags |
| TikTok Trending Searches | TikTok Trending Searches |
| TikTok Shop Hot Products | TikTok Shop Hot Products |
| YouTube Trending | YouTube Trending |
| X (Twitter) Trending | X (Twitter) Trending |
| Reddit Hot Posts | Reddit Hot Posts |
| Reddit World News | Reddit World News |
| Wikipedia Trending | Wikipedia Trending |
| Amazon Best Sellers Top Rated | Amazon Best Sellers Top Rated |
| Amazon Best Sellers by Category | Amazon Best Sellers by Category |
| App Store Top Free | App Store Top Free |
| App Store Top Paid | App Store Top Paid |
| Google Play | Google Play |
| Top Websites | Top Websites |
| Spotify Top Podcasts | Spotify Top Podcasts |
| Steam Most Played | Steam Most Played |
| GitHub Trending Repos | GitHub Trending Repos |
| IMDb MOVIEmeter | IMDb MOVIEmeter |
| Open Library Trending Books | Open Library Trending Books |
Page view volume for any article or topic as a normalized time series, growth percentages over 3M/6M/12M/5Y windows, and the live Wikipedia Trending feed of most-viewed articles today.
The Wikimedia API returns raw counts you must normalize and window yourself. Trends API returns a rescaled 0-100 series with growth already computed, in the same shape as 14 other sources - so cross-platform attention comparisons take one line of code.
It is one of the cleaner ones: page views are driven by active curiosity rather than algorithmic feeds, so spikes usually reflect genuine public attention events.
Updated through the day. Every response includes its own timestamp.
Yes - query both sources with the same keyword and compare normalized scores directly.
- Docs & quickstart: https://trendsapi.ai/#quickstart
- llms.txt (machine-readable API reference): https://trendsapi.ai/llms.txt
- Pricing (free tier: 100 requests/month): https://trendsapi.ai/#pricing
- Get an API key: https://trendsapi.ai/#get-key
MIT - see LICENSE. Data is served by Trends API; usage of the API itself is subject to the plan limits on your key.