Wikipedia Trends API
Wikipedia page view trends for any topic over time. Free key at trendsapi.ai
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
claude mcp add --transport http wikipedia-trends-api 'https://wikipedia.api.trendsapi.ai/mcp' --header 'Authorization: <Bearer token. Get your free API key at https://trendsapi.ai>'
{
"mcpServers": {
"wikipedia-trends-api": {
"type": "http",
"url": "https://wikipedia.api.trendsapi.ai/mcp",
"headers": {
"Authorization": "<Bearer token. Get your free API key at https://trendsapi.ai>"
}
}
}
}
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
Contents
Wikipedia page-view trends API
Wikipedia article attention via the Trends API. History, growth, and live trending pages as 0-100 scores.
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
| Method | REST mode | Returns |
|---|---|---|
get_time_series(keyword, source=, data_mode=) | get_time_series | list[TrendsDataPoint] |
get_growth(keyword, percent_growth=, source=, data_mode=) | get_growth | GetGrowthResponse |
get_live(limit=, offset=, category=) | get_top_trends | GetTopTrendsResponse |
get_top_trends(type=, ...) | get_top_trends | GetTopTrendsResponse |
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:
| Field | Always | Meaning |
|---|---|---|
date | yes | YYYY-MM-DD |
value | yes | 0-100 index for this series |
keyword | yes | Echo |
volume | no | Absolute volume when available |
source or datatype | no | Pipeline 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"}.
| Field | Meaning |
|---|---|
search_term | Keyword |
data_source | Source |
results | One object per window (period, growth, direction, dates, values) |
metadata | Counts / 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)
| Field | Meaning |
|---|---|
as_of_ts | Snapshot time |
type | Feed name |
limit, offset, count | Pagination |
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)
| Field | Value |
|---|---|
| Endpoint | POST https://api.trendsapi.ai/api |
| Auth | Authorization: Bearer $TRENDSAPI_KEY |
| History | source: wikipedia with get_time_series or get_growth |
| Keyword | Article title or topic, e.g. large language model |
Live type | Wikipedia 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.
JavavsJava (programming language)are different series. - Do not pass
source: wikipediaonget_top_trends. Usetype: Wikipedia Trending.
Errors
| HTTP | Client |
|---|---|
| 200 | Parsed payload. Python dataclasses / JS typed objects |
| 400 | Raises. Fix source or type spelling |
| 401 | Raises. Check TRENDSAPI_KEY |
| 404 | Raises. No series for that keyword. Do not retry |
| 429 | Raises. Quota |
| 5xx | Client 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.
Frequently asked questions
What is Wikipedia Trends API?
Wikipedia page view trends for any topic over time. Free key at trendsapi.ai
How do I install Wikipedia Trends API?
It runs as a remote server. In Claude Code: claude mcp add --transport http wikipedia-trends-api 'https://wikipedia.api.trendsapi.ai/mcp' --header 'Authorization: <Bearer token. Get your free API key at https://trendsapi.ai>'. For other clients, paste the JSON configuration from this page into their MCP settings.
Does Wikipedia Trends API need an API key?
Yes. It expects Authorization, which you set in its configuration.
Is Wikipedia Trends API open source?
Yes. Its code is on GitHub under the MIT license.
Who maintains Wikipedia Trends API?
It is published by trendsapi-ai. AI.tn lists it but does not maintain or endorse it.
From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.