MCP server for synthetic-consumer concept testing - Claude roleplays your target market, Semantic Similarity Rating (Maier et al. 2025) turns reactions into purchase-intent distributions
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Updated
Jun 16, 2026 - Python
MCP server for synthetic-consumer concept testing - Claude roleplays your target market, Semantic Similarity Rating (Maier et al. 2025) turns reactions into purchase-intent distributions
Predicting consumer purchase intentions using cognitive determinants, machine learning, and natural language processing.
Live demand and product trend data for AI ecommerce agents. Amazon, Google Shopping, TikTok, Reddit, App Store. Free tier.
See your product through your buyers' eyes — an agent skill that runs synthetic purchase-intent panels (SSR method, arXiv:2510.08338) against any website or product concept
amazon-trends-agent - Python agent package for TrendsMCP. Powered by trendsmcp.ai
Machine-learning workflow for predicting customer purchase intent with feature engineering, model comparison, and ensemble scoring.
Live consumer demand data for AI market research agents. Amazon, Google Shopping, TikTok, Reddit, App Store. Free tier.
Machine learning project for predicting e-commerce purchase intent from online shopper session behavior.
Amazon product search volume trends as a Python API client and MCP tool. Weekly series, growth percentages, and live best sellers. No Amazon API key. Powered by trendsmcp.ai
End-to-end clickstream ML pipeline for predicting cart conversion with leakage-safe features, XGBoost, Optuna, Streamlit, and Docker.
MCP server for live Amazon product search volume. Track consumer purchase intent and demand trends from Claude, Cursor, VS Code and more.
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