trendsMCP___get_growth
Analyze growth trends in normalized (0-100 scale) alternative data for investment intelligence. Calculates point-to-point growth comparing two specific data points. Supports preset time periods (12M, 6M, 3M, YTD, etc.) that automatically calculate dates, or custom date comparisons for precise analysis. All data is normalized on a 0-100 relative scale for consistent cross-platform comparison. Returns percentage change, volume metrics, data quality indicators, and exact dates used. Ideal for tracking brand momentum, market trends, competitive intelligence, and validating investment hypotheses across Google Search (search volume), Google Images (image search volume), Google News (news search volume), Google Shopping (shopping search volume), YouTube (video search volume), Wikipedia (page views), TikTok (hashtag volume), Amazon (product search volume), News Sentiment (news article sentiment analysis), and News Volume (news article volume intensity).
trendsMCP___get_ranked_trends
Retrieve ranked top trends using precomputed growth columns from the latest materialized views. Supports keyword, catalysts, companySingle, and companyCombined modes. Returns a ranked list with growth metrics and optional filters for datatype, volume, quality, and company metadata.
trendsMCP___get_top_trends
Retrieve the current top trending items for a specific data source. Returns the latest ranked list for the requested type.
trendsMCP___get_trends
Retrieve normalized (0-100 scale) historical time series data for detailed analysis. Returns full historical data points with values normalized on a 0-100 relative scale and absolute volume metrics when available. All trend values are normalized for consistent cross-temporal and cross-platform comparison. Use this when you need granular data points for custom calculations, charting, or time series modeling. Each data point includes date, normalized trend value (0-100), search volume, keyword, and data source. Provides approximately 5 years of weekly data or 1 month of daily data depending on mode. For most growth and trend questions, prefer get_growth which provides calculated metrics and insights. Best suited for quantitative researchers, data scientists, and analysts requiring raw normalized data for proprietary analysis.