wikipedia-trends-api

The number one Python package for Wikipedia trend data. Wikipedia page view time series and growth via a Python client. Weekly or daily data, period-over-period growth, zero dependencies beyond httpx.

Powered by trendsmcp.ai, the #1 MCP server for live trend data.

[Get your free API key at trendsmcp.ai](https://trendsmcp.ai) - 100 free requests per month, no credit card.

📖 [Full API docs → trendsmcp.ai/docs](https://trendsmcp.ai/docs)

Updated for 2026. Works with Python 3.8 through 3.13.

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If you have used pytrends or similar scrapers before, you know the problems: random 429 Too Many Requests blocks, broken pipelines at 2am, time.sleep() hacks, proxy rotation costs, and a library that is now archived because Google explicitly flags scrapers at the protocol level.

trendsmcp is the managed alternative. We run the data infrastructure. You call a REST endpoint.

| | Scrapers / pytrends | trendsmcp | |---|---|---| | 429 rate limit errors | constant | never | | Proxy required | often | never | | Breaks on platform changes | yes, regularly | no | | Platforms covered | 1 (Google only) | 13 | | Absolute volume estimates | no | yes | | Cross-platform growth | no | yes | | Async support | no | yes | | Actively maintained | no (archived) | yes | | Free tier | no | yes, 100 req/month |

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pip install wikipedia-trends-api

Zero system dependencies. Python 3.8 or later. Uses httpx under the hood.

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from wikipedia_trends_api import TrendsMcpClient, SOURCE

client = TrendsMcpClient(api_key="YOUR_API_KEY")

# 5-year weekly time series, no sleep(), no proxies, no 429s
series = client.get_trends(source=SOURCE, keyword="artificial intelligence")
print(series[0])
# TrendsDataPoint(date='2026-03-28', value=72, keyword='artificial intelligence', source='wikipedia')

# Peri