MCP Server

App store trend signals for AI agents

Understand mobile app store momentum for any app or category. Which apps are climbing in installs? Which categories are growing fastest? App store trend data gives your AI mobile market intelligence without an app store API.

Get started

Get your free API key

100 free requests/day. No credit card required.

Connect

Add to your AI in 30 seconds

An API key is required to connect. Get your free key above, then copy the pre-filled config for your client.

"trends-mcp": {
  "url": "https://api.trendsmcp.ai/mcp",
  "transport": "http",
  "headers": { "Authorization": "Bearer YOUR_API_KEY" }
}

+ Add to Cursor
Or paste into Mac / Linux — ~/.cursor/mcp.json
Windows — %USERPROFILE%\.cursor\mcp.json

↑ Get your free key above first — the config won't work without it.

claude.ai (Pro / Max / Team) — no JSON needed

https://api.trendsmcp.ai/mcp

Settings → Connectors → Add custom connector → paste URL above

Claude Desktop — add inside mcpServers

"trends-mcp": {
  "url": "https://api.trendsmcp.ai/mcp",
  "transport": "http",
  "headers": { "Authorization": "Bearer YOUR_API_KEY" }
}

Mac — ~/Library/Application Support/Claude/claude_desktop_config.json
Windows — %APPDATA%\Claude\claude_desktop_config.json

Fully quit and restart Claude Desktop after saving.

Add inside mcpServers

"trends-mcp": {
  "url": "https://api.trendsmcp.ai/mcp",
  "transport": "http",
  "headers": { "Authorization": "Bearer YOUR_API_KEY" }
}

Mac / Linux — ~/.codeium/windsurf/mcp_config.json
Windows — %USERPROFILE%\.codeium\windsurf\mcp_config.json
Or: Command Palette → Windsurf: Configure MCP Servers

Add inside servers — VS Code uses different key names

"trends-mcp": {
  "type": "http",
  "url": "https://api.trendsmcp.ai/mcp",
  "headers": { "Authorization": "Bearer YOUR_API_KEY" }
}

Paste into .vscode/mcp.json, or:
Command Palette (⇧⌘P / Ctrl+Shift+P) → MCP: Add Server

Data Sources

What you can query

All data is normalized to a 0-100 scale for consistent cross-platform comparison.

Google Trends

Search volume & Google News & Images

YouTube

Video search volume

TikTok

Hashtag volume trends

Community discussion volume

Amazon

Product search volume

Wikipedia

Page view trends

News

Volume + sentiment scores

Google Shopping

Shopping search volume

Web Traffic

Site visits via SimilarWeb

App Downloads

Android installs via AppBrain

Steam

Concurrent player counts

npm

Package weekly downloads

Tools

What your AI can call

Four tools. Your AI picks the right one automatically based on what you ask.

get_trends

Historical time series

Raw normalized data for a single source. Weekly mode returns ~5 years of data; daily mode returns the last 30 days. Each data point includes date, normalized value (0-100), and absolute volume where available. Best for charting, custom calculations, and time series modeling. Note: one source per call.

get_growth

Growth metrics

Point-to-point growth for preset periods (7D, 14D, 1M, 3M, 6M, 1Y, YTD, and more) or custom date ranges. Returns % change, volume, direction, and data quality score. Use source='all' for cross-platform aggregated growth, or pass comma-separated sources like 'amazon, tiktok, youtube' for multi-source comparison in one call.

get_growth(keyword='com.openai.chatgpt', source='app downloads', percent_growth=['6M', '1Y'])

get_ranked_trends

Ranked trend lists

Precomputed ranked lists of top trending keywords or companies. Supports keyword, catalyst, company (single), and company (combined) modes. Filter by sector, industry, country, earnings dates, minimum volume, and data quality. Sort by latest value, week-over-week, month-over-month, or year-over-year growth.

get_top_trends

Live trending now

What is trending right now with no keyword required. Covers: Google Trends, TikTok Trending Hashtags, Reddit Hot Posts, Wikipedia Trending, X (Twitter), App Store Top Free & Paid, Google Play, Spotify Top Podcasts, Google News, SimilarWeb Top Websites, and Amazon Best Sellers.

Outputs

What you get back

Normalized value

0-100 scale, consistent across all platforms

Absolute volume

Raw search / view counts where available

Growth %

Period-over-period change with exact dates

Time series

Up to 5 years of weekly data per keyword

Data quality

Coverage score and zero-value detection

Multi-source

get_growth supports 'all' or comma-separated sources in one call

FAQ

Common questions

How is app store trend data structured?

JSON with normalized install trend (0-100), growth percentage over the selected period, and a weekly time series. Includes a data quality score based on app install volume.

Can I compare multiple apps side by side?

Yes. Call get_growth for each bundle ID and compare the results -- useful for competitive analysis of apps in the same category.

Why do I need a bundle ID instead of the app name?

The underlying AppBrain data is indexed by Android package name (bundle ID), not display names. Example: 'com.whatsapp' for WhatsApp, 'com.instagram.android' for Instagram.