← Discover MCPs and Agents
W
MCPAI & MLMCP Registry

Wikipedia Trends API

Wikipedia page view trends for any topic over time. Free key at trendsapi.ai

Links

README

From the repo.

Wikipedia page-view trends API

Wikipedia article attention via the Trends API. History, growth, and live trending pages as 0-100 scores.

License: MIT PyPI Python

Key: trendsapi.ai/#get-key. HTTP contract and every source: trendsapi-ai/trendsapi.

Authentication

pip install trendsapi-wikipedia
export TRENDSAPI_KEY=your_key

Python 3.9+. Same key as the HTTP API.

from trendsapi_wikipedia import TrendsAPI

client = TrendsAPI()                    # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")

Keyword helpers default to source: "wikipedia". Pass source= to hit any other platform with the same client. Official full client (every source, no preset): trendsapi.

Methods

MethodREST modeReturns
get_time_series(keyword, source=, data_mode=)get_time_serieslist[TrendsDataPoint]
get_growth(keyword, percent_growth=, source=, data_mode=)get_growthGetGrowthResponse
get_live(limit=, offset=, category=)get_top_trendsGetTopTrendsResponse
get_top_trends(type=, ...)get_top_trendsGetTopTrendsResponse

source is lowercase (wikipedia). type is exact (Wikipedia Trending). Mixing them is a 400.

from trendsapi_wikipedia import TrendsAPI

client = TrendsAPI()                    # TRENDSAPI_KEY
# client = TrendsAPI(api_key="YOUR_KEY")

series = client.get_time_series("large language model")
print(series[-1].date, series[-1].value)

growth = client.get_growth("large language model", percent_growth=["3M", "12M"])
print(growth.results[0].growth, growth.results[0].direction)

hot = client.get_live(limit=10)
print(hot.data)                         # [[1, "..."], ...]

get_time_series

points = client.get_time_series("large language model")

Each point:

FieldAlwaysMeaning
dateyesYYYY-MM-DD
valueyes0-100 index for this series
keywordyesEcho
volumenoAbsolute volume when available
source or datatypenoPipeline label

Python returns list[TrendsDataPoint]. Use .date and .value, not ["date"]. JS returns the same fields as object properties.

get_growth

g = client.get_growth("large language model", percent_growth=["12M", "3M", "YTD"])
print(g.results[0].growth, g.results[0].direction)

percent_growth default: ["12M"]. Presets: 7D 14D 30D 1M 2M 3M 6M 9M 12M/1Y 18M 24M/2Y 36M/3Y 48M 60M/5Y MTD QTD YTD. Custom: {"name": "Launch", "recent": "2024-06-01", "baseline": "2024-01-01"}.

FieldMeaning
search_termKeyword
data_sourceSource
resultsOne object per window (period, growth, direction, dates, values)
metadataCounts / success flag

Several windows still count as one request. Python: growth.results[0].growth. JS: growth.results[0].growth.

get_live

hot = client.get_live(limit=10)
FieldMeaning
as_of_tsSnapshot time
typeFeed name
limit, offset, countPagination
data[rank, label] rows

Python: hot.data. JS: hot.data. Optional offset= and category= (Amazon Best Sellers by Category, Top Websites only).

Async

import asyncio
from trendsapi_wikipedia import AsyncTrendsAPI

async def main():
    c = AsyncTrendsAPI()
    return await asyncio.gather(
        c.get_time_series("large language model"),
        c.get_time_series("large language model", source="google search"),
    )

asyncio.run(main())

Each 200 is one billed request.

Pandas

from dataclasses import asdict
import pandas as pd
from trendsapi_wikipedia import TrendsAPI

df = pd.DataFrame(asdict(p) for p in TrendsAPI().get_time_series("large language model"))
df["date"] = pd.to_datetime(df["date"])
print(df.set_index("date")["value"].resample("ME").mean().tail())

Call (curl)

FieldValue
EndpointPOST https://api.trendsapi.ai/api
AuthAuthorization: Bearer $TRENDSAPI_KEY
Historysource: wikipedia with get_time_series or get_growth
KeywordArticle title or topic, e.g. large language model
Live typeWikipedia Trending
curl -sS -X POST https://api.trendsapi.ai/api \
  -H "Authorization: Bearer $TRENDSAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"mode":"get_time_series","source":"wikipedia","keyword":"large language model"}'

Source notes

  • Titles are picky. Java vs Java (programming language) are different series.
  • Do not pass source: wikipedia on get_top_trends. Use type: Wikipedia Trending.

Errors

HTTPClient
200Parsed payload. Python dataclasses / JS typed objects
400Raises. Fix source or type spelling
401Raises. Check TRENDSAPI_KEY
404Raises. No series for that keyword. Do not retry
429Raises. Quota
5xxClient retries, then raises

The HTTP body field is a JSON string. SDKs decode it. Raw curl must parse body a second time.

Site: https://trendsapi.ai/trends/wikipedia-trends.

License

MIT. See LICENSE.

Config for your environment

Use the endpoint URL below in your config. No API key — you connect directly.

Tool

OS

Config file: ~/.cursor/mcp.json

{
  "mcpServers": {
    "mcp-server": {
      "url": "https://wikipedia.api.trendsapi.ai/mcp"
    }
  }
}

Paste into mcpServers in the config file. Restart Cursor after saving.

If this MCP is also published on mcpchannel.ai, you can subscribe from Browse and use the gateway config there instead.