Subconscious Ai Mcp
About
Run conjoint experiments and causal research through AI-powered behavioral simulations
Details
- Author
- subconscious-ai
- Downloads
- 163
- Categories
- Productivity, Other, AI
Jump to
- Causal research: validate research questions and generate statistically valid experiments
- Synthetic populations: AI personas based on US Census microdata (IPUMS)
- Conjoint analysis: AMCE for measuring attribute importance
- Works with Claude Desktop, Cursor, and any MCP-compatible client
- REST API with direct HTTP access for integrations (n8n, Zapier)
- Real-time updates via Server-Sent Events for live experiment progress
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
Subconscious Ai McpCommand (node, npx, python, etc.)Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
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.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"subconscious ai mcp": {
"subconscious-ai": {
"url": "https://ghostshell-runi.vercel.app/api/sse?token=YOUR_TOKEN"
}
}
}
}McpServers
{
"subconscious-ai": {
"url": "https://ghostshell-runi.vercel.app/api/sse?token=YOUR_TOKEN"
}
}Subconscious AI MCP Server
Run AI-powered conjoint experiments from Claude, Cursor, or any MCP-compatible client. Understand why people make decisions using causal inference and synthetic populations.
✨ Features
- 🧠 Causal Research - Validate research questions and generate statistically valid experiments
- 👥 Synthetic Populations - AI personas based on US Census microdata (IPUMS) for representative sampling
- 📊 Conjoint Analysis - AMCE (Average Marginal Component Effects) for measuring attribute importance
- 🤖 MCP Protocol - Works with Claude Desktop, Cursor, and any MCP-compatible AI assistant
- 🌐 REST API - Direct HTTP access for integrations (n8n, Zapier, custom apps)
- ⚡ Real-time Updates - Server-Sent Events (SSE) for live experiment progress
🚀 Quick Start
Option 1: Use Hosted Server (Recommended)
No setup required! Add to your MCP client configuration:
Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json):
{
"mcpServers": {
"subconscious-ai": {
"url": "https://ghostshell-runi.vercel.app/api/sse?token=YOUR_TOKEN"
}
}
}
Cursor (~/.cursor/mcp.json):
{
"mcpServers": {
"subconscious-ai": {
"url": "https://ghostshell-runi.vercel.app/api/sse?token=YOUR_TOKEN"
}
}
}
> 🔑 Get your token at app.subconscious.ai → Settings → Access Token
Option 2: Run Locally
Prerequisites:
- Python 3.11+
- A Subconscious AI account and Access token
```bash
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