Enables AI-powered conjoint experiments and causal research through an MCP server compatible with various AI assistants.
Sponsored
Ghostshell functions as an MCP (Model Context Protocol) server, allowing AI assistants like Claude Desktop and Cursor to perform sophisticated causal research and conjoint analysis. It leverages synthetic populations, generated from US Census microdata, to construct statistically valid experiments for understanding human decision-making. The server provides a comprehensive suite of tools for validating research questions, generating experiment attributes, creating and managing experiments, and retrieving detailed analytical insights, accessible via both MCP clients and a direct REST API for seamless integration.
Key Features
01Synthetic Populations for Representative Sampling
02Conjoint Analysis (AMCE) for Attribute Importance
03MCP Protocol Compatibility with AI Assistants
04Causal Research & Experiment Validation
05REST API for Direct Integrations
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Use Cases
01Validating causal research questions for AI-driven studies.
02Generating AI-powered attributes and levels for market research experiments.
03Conducting and analyzing conjoint experiments with synthetic respondents to understand decision-making.