news-volume-mcp
Provides Amazon product search volume trends and best sellers data for market research and consumer demand analysis.
Provides App Store interest trends and app download estimates alongside other platform data.
Supports wrapping trend methods as tools for use within CrewAI agent crews.
Provides Google Search volume trends for keyword research and SEO analysis.
Provides Google News search volume trends and a live Google News trending feed.
Provides Google Play store interest trends alongside other app store data.
Allows passing TrendsMcpClient output directly as tool results or context in LangChain applications.
Provides npm package weekly download trends for open-source package analysis.
Supports converting trend series responses to pandas DataFrames for data analysis.
The package itself is distributed via PyPI, enabling installation through pip.
Provides a Python client library for accessing news volume and trend data programmatically.
Provides Reddit discussion volume and subreddit subscriber trends for community and investment research.
Provides Spotify top podcasts feed and trending data.
Provides Steam concurrent player count trends for game market analysis.
Provides TikTok hashtag volume trends and trending hashtags data for content strategy.
Provides Wikipedia page view trends as leading indicators for topic interest.
Provides YouTube search volume trends and trending video data for content and SEO research.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@news-volume-mcpshow me the news volume growth for 'AI' over the past month"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
news-volume-mcp
News mention volume as an MCP tool. Plug into Claude, Cursor, or any MCP-compatible AI host. Weekly series, growth percentages, and live Google News feed.
Powered by trendsmcp.ai — one API key, one client, 30+ data sources: Google Search, YouTube, TikTok, Reddit, Amazon, Wikipedia, App Store, Steam, npm, news volume, news sentiment, live trending feeds, and more. No separate credentials per platform.
Get your free API key → trendsmcp.ai — 100 free requests/month, no credit card.
📖 Full API docs → trendsmcp.ai/docs
Updated for 2026. Works with Python 3.8 through 3.13.
Use as an MCP tool
Add to your mcp.json (Claude Desktop, Cursor, Windsurf, VS Code, or any MCP host):
{
"mcpServers": {
"trends-mcp": {
"url": "https://api.trendsmcp.ai/mcp",
"transport": "http",
"headers": { "Authorization": "Bearer YOUR_API_KEY" }
}
}
}Get your free key at trendsmcp.ai. Full setup instructions for Claude, Cursor, Windsurf, and VS Code at trendsmcp.ai/docs.
Related MCP server: news-volume-mcp
No scraping. No 429 errors. No proxies.
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.
pytrends alternative for News Volume data
Scrapers / pytrends | trendsmcp | |
429 rate limit errors | constant | never |
Proxy required | often | never |
Breaks on platform changes | yes, regularly | no |
Data sources covered | 1 (Google only) | 30+ |
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 |
Install
pip install news-volume-mcpZero system dependencies. Python 3.8 or later. Uses httpx under the hood.
Quick start
from news_volume_mcp 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="climate change")
print(series[0])
# TrendsDataPoint(date='2026-03-28', value=72, keyword='climate change', source='news volume')
# Period-over-period growth
growth = client.get_growth(
source=SOURCE,
keyword="climate change",
percent_growth=["3M", "1Y"],
)
print(growth.results[0])
# GrowthResult(period='3M', growth=14.5, direction='increase', ...)
# What's trending right now (across all live platforms)
trending = client.get_top_trends(limit=10)
print(trending.data)
# [[1, 'topic one'], [2, 'topic two'], ...]Async support
import asyncio
from news_volume_mcp import AsyncTrendsMcpClient, SOURCE
async def main():
client = AsyncTrendsMcpClient(api_key="YOUR_API_KEY")
series = await client.get_trends(source=SOURCE, keyword="climate change")
print(series[0])
asyncio.run(main())Query multiple platforms concurrently with one key:
google, youtube, reddit, amazon, tiktok = await asyncio.gather(
client.get_trends(source="google search", keyword="climate change"),
client.get_trends(source="youtube", keyword="climate change"),
client.get_trends(source="reddit", keyword="climate change"),
client.get_trends(source="amazon", keyword="climate change"),
client.get_trends(source="tiktok", keyword="climate change"),
)Use cases
SEO research: track keyword search volume trends across Google Search, Google News, and Google Images before publishing content
Market research: measure consumer demand signals on Amazon and Google Shopping before entering a product category
Investment research: monitor Reddit discussion volume, news sentiment, and Wikipedia page view spikes as leading indicators
Content strategy: find what is growing on YouTube and TikTok before topics peak and competition saturates them
Competitor tracking: compare brand search volume growth across platforms over custom date ranges
App analytics: track App Store interest and app download estimates alongside Reddit and news buzz
Works with
Claude (via MCP — trendsmcp.ai/docs)
Cursor (via MCP — trendsmcp.ai/docs)
ChatGPT (via MCP — trendsmcp.ai/docs)
Windsurf (via MCP — trendsmcp.ai/docs)
VS Code Copilot (via MCP — trendsmcp.ai/docs)
LangChain: pass
TrendsMcpClientoutput directly as tool results or contextCrewAI: wrap any method as a
Tooland drop it into your crewAutoGen: register as a callable tool for any agent
LlamaIndex: use trend series as structured data nodes for retrieval
Pandas: each
get_trends()response converts to a DataFrame in one line
Methods
get_trends(source, keyword, data_mode=None)
Returns a historical time series for a keyword. Defaults to 5 years of weekly data. Pass data_mode="daily" for the last 30 days at daily granularity.
get_growth(source, keyword, percent_growth, data_mode=None)
Calculates percentage growth between two points in time. Pass preset strings or CustomGrowthPeriod objects.
Growth presets: 7D 14D 30D 1M 2M 3M 6M 9M 12M 1Y 18M 24M 2Y 36M 3Y 48M 60M 5Y MTD QTD YTD
get_top_trends(type=None, limit=None)
Returns today's live trending items. Omit type to get all feeds at once.
Available live feeds: Google Trends Google News Top News YouTube Trending TikTok Trending Hashtags X (Twitter) Trending Reddit Hot Posts Reddit World News Wikipedia Trending Amazon Best Sellers Top Rated Amazon Best Sellers by Category App Store Top Free App Store Top Paid Google Play Spotify Top Podcasts Top Websites
All 30+ data sources
One API key. One client. Every platform. No separate credentials for each.
source | What it measures |
| Google Search volume |
| Google Images search volume |
| Google News search volume |
| Google Shopping purchase intent |
| YouTube search volume |
| TikTok hashtag volume |
| Reddit subreddit subscribers over time |
| Amazon product search volume |
| Wikipedia page views |
| News article mention count |
| News sentiment score (positive/negative) |
| Mobile app download/install estimates (Android) |
| npm package weekly downloads |
| Steam concurrent player count |
All values normalized 0–100 so you can compare across platforms directly.
Error handling
from news_volume_mcp import TrendsMcpClient, TrendsMcpError, SOURCE
client = TrendsMcpClient(api_key="YOUR_API_KEY")
try:
series = client.get_trends(source=SOURCE, keyword="climate change")
except TrendsMcpError as e:
print(e.status) # e.g. 429 if you exceed your plan quota
print(e.code) # e.g. "rate_limited"
print(e.message)Frequently asked questions
Does this scrape News Volume? No. trendsmcp runs managed data infrastructure. Your Python code makes a single authenticated REST call. No scraping, no Selenium, no cookies, no proxies required.
Do I need a News Volume developer account, OAuth token, or platform API key? No. One trendsmcp API key gives you access to all 30+ data sources.
Will it break when News Volume changes its backend? No. API stability is our responsibility. If something changes upstream, we update the backend. Your code keeps working.
Can I query multiple platforms with the same key?
Yes. One key covers every data source. Switch source to any of the 30+ values listed above.
Is there a free tier? Yes, 100 requests per month, no credit card required. Get your key at trendsmcp.ai.
Can I use this in production data pipelines? Yes. The client is stateless, thread-safe, and supports async for concurrent queries across multiple platforms.
Related packages
trendsmcp — core package, all 30+ data sources
youtube-trends-api / youtube-trends-mcp / youtube-trends-agent
google-search-trends-api / google-search-trends-mcp / google-search-trends-agent
wikipedia-trends-api / wikipedia-trends-mcp / wikipedia-trends-agent
app-store-trends-api / app-store-trends-mcp / app-store-trends-agent
news-sentiment-api / news-sentiment-mcp / news-sentiment-agent
Links
License
MIT
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