Wikipedia page view volume as a structured time series. Track how many people are looking up any topic on Wikipedia, measure growth over time, and get live trending articles - via a single POST endpoint.
The Wikimedia REST API makes raw page view counts available. The data is there, but working with it requires knowing exact article titles, handling the daily granularity, normalizing across topics yourself, and building your own growth calculations. That's enough friction that most teams skip it.
Trends MCP abstracts that into a single consistent endpoint. Topic phrase in, normalized time series out. Growth calculations included.
POST https://api.trendsmcp.ai/api
Authorization: Bearer YOUR_API_KEY
Content-Type: application/json
Weekly Wikipedia page view interest for any topic, normalized 0-100.
{
"source": "wikipedia",
"keyword": "artificial intelligence"
}
Response:
[
{
"date": "2026-03-21",
"value": 91,
"volume": null,
"keyword": "artificial intelligence",
"source": "wikipedia"
}
]
Daily mode for the last 30 days:
{
"source": "wikipedia",
"keyword": "artificial intelligence",
"data_mode": "daily"
}
{
"source": "wikipedia",
"keyword": "model context protocol",
"percent_growth": ["6M", "1Y", "2Y"]
}
Preset periods: 7D 14D 30D 1M 2M 3M 6M 9M 12M 1Y 18M 24M 2Y 36M 3Y 48M 60M 5Y MTD QTD YTD
Wikipedia page views are a useful proxy for public awareness. A topic that shows 300% growth in Wikipedia views over 12 months is entering mainstream consciousness - often before it peaks in Google Search. The lag between Wikipedia interest and broader search volume tends to be a few weeks to a few months.
{
"mode": "top_trends",
"type": "Wikipedia Trending",
"limit": 25
}
Python
import requests
res = requests.post(
"https://api.trendsmcp.ai/api",
headers={"Authorization": "Bearer YOUR_API_KEY"},
json={"source": "wikipedia", "keyword": "model context protocol", "percent_growth": ["1Y", "3Y"]}
)
data = res.json()
JavaScript
const res = await fetch("https://api.trendsmcp.ai/api", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json"
},
body: JSON.stringify({ source: "wikipedia", keyword: "model context protocol", percent_growth: ["1Y", "3Y"] })
});
const data = await res.json();
FAQ