trendsmcp 1.0.1

Python client for the Trends MCP API. Keyword trend time series and growth rates across Google Search, YouTube, Reddit, Amazon, TikTok, Wikipedia, npm, Steam, and more.

trendsmcp

Python client for the Trends MCP API. Get live keyword trend data across 13 platforms: Google Search, YouTube, Reddit, Amazon, TikTok, Wikipedia, npm, Steam, and more. One API key, one client, no scraping, no proxies, no 429 errors.

Powered by trendsmcp.ai.

Get a free API key - 100 requests/month, no credit card.

Full API docs

Works with Python 3.8 through 3.13.

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Install

pip install trendsmcp

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Connect

from trendsmcp import TrendsMcpClient

client = TrendsMcpClient(api_key="YOUR_API_KEY")

Get your key at trendsmcp.ai.

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get_trends

Returns a weekly time series for a keyword (5 years by default). Pass data_mode="daily" for the last 30 days at daily granularity.

series = client.get_trends(source="google search", keyword="bitcoin")

print(series[0])
# TrendsDataPoint(date='2021-01-03', value=12, volume=None, keyword='bitcoin', source='google search')

print(series[-1])
# TrendsDataPoint(date='2026-03-23', value=47, volume=None, keyword='bitcoin', source='google search')

# Daily granularity
series = client.get_trends(source="youtube", keyword="bitcoin", data_mode="daily")

Parameters

Parameter	Type	Description
source	str	Data source (see full list below)
keyword	str	Keyword to look up
data_mode	str	"weekly" (default) or "daily"

Returns a list of TrendsDataPoint objects:

Field	Type	Description
date	str	ISO date string
value	float	Normalized value 0-100
volume	float or None	Absolute volume estimate where available
keyword	str	The keyword queried
source	str	The data source

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get_growth

Returns period-over-period growth for a keyword. Pass preset strings or custom date pairs.

growth = client.get_growth(
    source="google search",
    keyword="nike",
    percent_growth=["3M", "12M", "YTD"],
)

print(growth.results[0])
# GrowthResult(period='3M', growth=14.5, direction='increase', ...)

for r in growth.results:
    print(f"{r.period}: {r.growth:+.1f}% ({r.direction})")

Growth presets: 7D 14D 30D 1M 2M 3M 6M 9M 12M 1Y 18M 24M 2Y 36M 3Y 48M 60M 5Y MTD QTD YTD

Custom date ranges:

from trendsmcp import TrendsMcpClient, CustomGrowthPeriod

growth = client.get_growth(
    source="amazon",
    keyword="air fryer",
    percent_growth=[
        CustomGrowthPeriod(name="holiday lift", recent="2025-12-31", baseline="2025-10-01")
    ],
)

Parameters

Parameter	Type	Description
source	str	Data source
keyword	str	Keyword to look up
percent_growth	list	List of preset strings or CustomGrowthPeriod objects
data_mode	str	"weekly" (default) or "daily"

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get_top_trends

Returns today's live trending items from platform feeds. Omit type to get all feeds at once.

# Single feed
trending = client.get_top_trends(type="Google Trends", limit=10)
print(trending.data)
# [[1, 'tiger woods'], [2, 'miley cyrus'], ...]

# All feeds at once
all_trending = client.get_top_trends()

Available feeds: Google Trends YouTube TikTok Trending Hashtags Reddit Hot Posts Amazon Best Sellers Top Rated App Store Top Free App Store Top Paid Wikipedia Trending Spotify Top Podcasts X (Twitter)

Parameters

Parameter	Type	Description
type	str	Feed name (omit for all feeds)
limit	int	Max items per feed, up to 200 (default 50)

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Async support

import asyncio
from trendsmcp import AsyncTrendsMcpClient

async def main():
    client = AsyncTrendsMcpClient(api_key="YOUR_API_KEY")

    # Run multiple platforms concurrently
    google, youtube, reddit = await asyncio.gather(
        client.get_trends(source="google search", keyword="AI"),
        client.get_trends(source="youtube", keyword="AI"),
        client.get_trends(source="reddit", keyword="AI"),
    )
    print(f"Google: {google[-1].value}  YouTube: {youtube[-1].value}  Reddit: {reddit[-1].value}")

asyncio.run(main())

All three methods (get_trends, get_growth, get_top_trends) have async equivalents on AsyncTrendsMcpClient.

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Error handling

from trendsmcp import TrendsMcpClient, TrendsMcpError

client = TrendsMcpClient(api_key="YOUR_API_KEY")

try:
    series = client.get_trends(source="google search", keyword="bitcoin")
except TrendsMcpError as e:
    print(e.status)   # HTTP status code, e.g. 429
    print(e.code)     # Machine-readable code, e.g. "rate_limited"
    print(e.message)  # Human-readable message

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Use with Pandas

import pandas as pd
from trendsmcp import TrendsMcpClient

client = TrendsMcpClient(api_key="YOUR_API_KEY")
series = client.get_trends(source="google search", keyword="bitcoin")
df = pd.DataFrame([vars(p) for p in series])
print(df.tail())

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All 13 supported sources

source	What it measures
"google search"	Google Search volume
"google images"	Google Images search volume
"google news"	Google News search volume
"google shopping"	Google Shopping purchase intent
"youtube"	YouTube search volume
"tiktok"	TikTok hashtag volume
"reddit"	Reddit mention volume
"amazon"	Amazon product search volume
"wikipedia"	Wikipedia page views
"news volume"	News article mention count
"news sentiment"	News sentiment score
"npm"	npm package weekly downloads
"steam"	Steam concurrent player count

All values are normalized 0 to 100 so you can compare across platforms directly.

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Why not pytrends?

pytrends scrapes Google and has been archived since 2023. It breaks regularly, returns 429 errors, requires proxies, and only covers Google Search with relative scores (0 to 100), no absolute volume.

trendsmcp is a managed REST API. No scraping, no 429s, no proxies required, 13 platforms, absolute volume estimates, and actively maintained.

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Related packages

Platform-specific packages that expose the same client with a pre-set SOURCE constant:

• youtube-trends-api
• reddit-trends-api
• google-search-trends-api
• amazon-trends-api
• tiktok-trends-api
• wikipedia-trends-api
• npm-trends-api
• steam-trends-api
• app-store-trends-api
• news-volume-api
• news-sentiment-api

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License

MIT