MCP Server

Search trend API for developers

A search trend API designed from the ground up for AI agents and developers. Unlike fragile web scrapers or Google's unofficial pytrends library, Trends MCP provides a stable, normalized, MCP-native interface to search trend data across Google, YouTube, Amazon, and 9 more sources.

Get your free API key

100 free requests/day. No credit card required.

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

What you can query

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

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_trends(keyword='next.js', source='google search', data_mode='weekly')
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_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.

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

Common questions

For each query: normalized interest values (0-100), absolute volume estimates, week-by-week or month-by-month time series, growth percentages, and data quality scores. All returned as structured JSON compatible with any AI agent tool-calling interface.
Trends MCP is delivered as a Model Context Protocol server, which means AI agents connect to it directly using the MCP standard. For direct REST access, the underlying API endpoint is also available at api.trendsmcp.ai.
pytrends scrapes the Google Trends website and breaks whenever Google changes its frontend. Trends MCP uses a managed data pipeline with built-in retries, rate-limit handling, and fallback sources. It is designed for production AI agent use, not one-off scripts.
Yes. Many teams use Trends MCP to feed their AI writing workflows with live keyword trend data -- identifying growing topics before writing about them and validating content angles with real search momentum data.