Wikipedia page view data for AI agents

Structured Wikipedia traffic data for any topic, delivered to your AI. Measure information-seeking volume, detect sudden spikes from news events, and correlate with search and social signals across the same timeline.

get_trends

Export the raw weekly Wikipedia page view time series - each point includes date, normalized traffic, and absolute view count estimate for custom event-correlation analysis.

get_trends(keyword='nuclear fusion', source='wikipedia', data_mode='weekly')

get_growth

Calculate Wikipedia page view growth to quantify how much information-seeking has increased around a topic - useful for validating whether a news story is driving durable curiosity or a one-day spike.

get_growth(keyword='nuclear fusion', source='wikipedia', percent_growth=['1M', '3M'])

get_ranked_trends

Find the fastest-growing Wikipedia articles by page view growth - surfaces topics where information demand is accelerating, often a leading indicator that a subject is about to enter mainstream discourse.

get_ranked_trends(source='wikipedia', sort='mom_pct_change', limit=25)

get_top_trends

Pull Wikipedia's live trending articles to see which topics people are rushing to look up right now - one of the clearest signals of breaking public curiosity.

get_top_trends(type='Wikipedia Trending', limit=25)

Common questions

JSON with normalized page traffic (0-100), absolute view count estimates, growth percentage, and a weekly time series. Includes a data quality score based on article traffic volume.
Yes. A sudden spike in Wikipedia page views is often the earliest detectable signal that a topic has entered public consciousness. Combine with get_top_trends for real-time detection.
They measure different things. Google Search captures active intent (people looking something up). Wikipedia page views capture passive curiosity - readers who clicked through from a news article or social post. A spike in Wikipedia views that does not show up in Google Search often indicates a story is driving awareness rather than active purchase or investment intent, making it a useful signal for separating noise from genuine demand.