MCP Server

Google Trends API for AI agents

The official Google Trends site has no public API. Trends MCP fills that gap: structured Google Search trend data delivered to any AI assistant via the Model Context Protocol. Absolute volume estimates, multi-source comparison, 5-year history -- all in one clean JSON response.

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
Reddit
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='model context protocol', source='google search', percent_growth=['3M', '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

No. Google Trends has no official public API. The website provides relative interest data with no programmatic access. Trends MCP provides a structured, AI-native alternative that returns absolute volume estimates, growth metrics, and historical time series via the Model Context Protocol.
pytrends is a Python library that scrapes the Google Trends website, returns only relative (0-100) interest scores, and is subject to rate limiting and breakage when Google changes its frontend. Trends MCP returns absolute volume estimates, supports multi-source queries across 12+ platforms in one call, and is designed for AI agents rather than Python scripts.
Yes. Trends MCP adds absolute query volume estimates alongside the normalized 0-100 signal. These are directionally accurate for trend analysis -- suitable for comparing keyword momentum, not for ad campaign budgeting.
A structured object with: keyword, source, normalized_value (0-100), absolute_volume_estimate, growth_pct (per period), time_series (array of date/value pairs), and data_quality_score.
Trends MCP operates within your plan's query limits. Unlike scraping pytrends, there are no IP-based rate limits or Google bot-detection issues to manage.

Explore more

Google Trends data for AI assistants A modern pytrends alternative for AI agents The Google Trends alternative built for AI All data sources