What runtime and dependencies are required?
Python 3.11+ is required for local execution. Dependencies are listed in `requirements.txt` and installed via pip.
@subconscious-ai
基本信息
Run conjoint experiments and causal research through AI-powered behavioral simulations
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"subconscious-ai": {
"url": "https://ghostshell-runi.vercel.app/api/sse?token=YOUR_TOKEN"
}
}
}工具列表暂未提供
当前收录暂时没有可展示的工具列表,不代表服务没有工具。请查阅项目文档了解支持的能力。
此服务需要认证,获取工具列表可能需要登录或使用服务提供方的凭据。
点击上方按钮,直接连接服务器端点实时获取工具列表。
Subconscious Ai Mcp is an MCP (Model Context Protocol) server that lets you run AI-powered conjoint experiments from Claude Desktop, Cursor, or any MCP-compatible client. It uses causal inference and synthetic populations based on US Census microdata to help understand why people make decisions.
You can use the hosted server by adding a URL with a token to your MCP client configuration (Claude Desktop or Cursor), or run it locally by cloning the repo, installing dependencies with Python 3.11+, and setting environment variables AUTH0_JWT_TOKEN and API_BASE_URL. Tokens are obtained from app.subconscious.ai.
Python 3.11+ is required for local execution. Dependencies are listed in `requirements.txt` and installed via pip.
You need an active Subconscious AI subscription. For the hosted server, include your token as a query parameter in the SSE URL. For local setup, set the `AUTH0_JWT_TOKEN` environment variable.
The server proxies requests to the Subconscious AI backend (`https://api.subconscious.ai`). Self-hosted deployments also route through this backend; user data is not stored on the MCP server itself.
The server supports MCP via SSE (Server-Sent Events) and also provides a REST API at `/api/call/{tool}` endpoints. Both require authentication.
The README mentions experiments can be created with a specified confidence level (e.g., "Reasonable"), but does not state explicit quantitative limits. The platform surveys synthetic respondents (e.g., 500 per experiment).

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