app-store-trends-mcp

App download trends as an MCP tool. Plug into Claude, Cursor, or any MCP-compatible AI host. Weekly series, growth percentages, and live top charts.

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.

Quick install

Same four clients as the site hero. Get a free key first (100 req/mo). Claude and ChatGPT sign you in with OAuth. Cursor and VS Code: click, then put your key from /account if the deeplink used a placeholder.

Then ask: Using TrendsMCP, what's trending on Google right now?

Related MCP server: GetAppNiche MCP

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.

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 App Store data

Install

pip install app-store-trends-mcp

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

Quick start

from app_store_trends_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="com.openai.chatgpt")
print(series[0])
# TrendsDataPoint(date='2026-03-28', value=72, keyword='com.openai.chatgpt', source='app downloads')

# Period-over-period growth
growth = client.get_growth(
    source=SOURCE,
    keyword="com.openai.chatgpt",
    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 app_store_trends_mcp import AsyncTrendsMcpClient, SOURCE

async def main():
    client = AsyncTrendsMcpClient(api_key="YOUR_API_KEY")
    series = await client.get_trends(source=SOURCE, keyword="com.openai.chatgpt")
    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="com.openai.chatgpt"),
    client.get_trends(source="youtube",       keyword="com.openai.chatgpt"),
    client.get_trends(source="reddit",        keyword="com.openai.chatgpt"),
    client.get_trends(source="amazon",        keyword="com.openai.chatgpt"),
    client.get_trends(source="tiktok",        keyword="com.openai.chatgpt"),
)

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 TrendsMcpClient output directly as tool results or context

• CrewAI: wrap any method as a Tool and drop it into your crew

• AutoGen: 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.

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

Error handling

from app_store_trends_mcp import TrendsMcpClient, TrendsMcpError, SOURCE

client = TrendsMcpClient(api_key="YOUR_API_KEY")

try:
    series = client.get_trends(source=SOURCE, keyword="com.openai.chatgpt")
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 App Store? 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 App Store 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 App Store 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

• reddit-trends-api / reddit-trends-mcp / reddit-trends-agent

• google-search-trends-api / google-search-trends-mcp / google-search-trends-agent

• amazon-trends-api / amazon-trends-mcp / amazon-trends-agent

• tiktok-trends-api / tiktok-trends-mcp / tiktok-trends-agent

• wikipedia-trends-api / wikipedia-trends-mcp / wikipedia-trends-agent

• npm-trends-api / npm-trends-mcp / npm-trends-agent

• steam-trends-api / steam-trends-mcp / steam-trends-agent

• app-store-trends-api / app-store-trends-mcp / app-store-trends-agent

• news-volume-api / news-volume-mcp / news-volume-agent

• news-sentiment-api / news-sentiment-mcp / news-sentiment-agent

Links

• API docs

• Get a free API key

• pytrends alternative

• All packages on PyPI

• GitHub

License

MIT