MCP Server

Reddit discussion trend data for AI

Measure how much Reddit is talking about any topic. Community discussion volume, growing subreddit interest, and historical activity data - all queryable from your AI without hitting Reddit API limits.

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='electric vehicles', source='reddit', 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

Reddit discussion volume trends - normalized interest in a topic across the platform over time, including growth rate and historical time series. Not raw post counts, but a normalized demand signal calibrated for trend comparison.
For volume signals, yes. Trends MCP shows whether discussion around a brand is growing or shrinking. For sentiment, the News source gives sentiment scores; Reddit gives pure volume context.
The current signal is platform-wide Reddit discussion volume for a keyword. Subreddit-level filtering is on the roadmap.
Reddit often reflects niche, enthusiast, and early-adopter communities before topics reach mainstream Google Search. Comparing both reveals whether interest is still underground or going mainstream.