mcp-subconscios

mcp-subconscios

Run conjoint experiments and causal research through AI powered behavioral simulations

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README

Subconscious AI MCP Server

License: Proprietary Python 3.11+ MCP Protocol

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
# Clone the repository
git clone https://github.com/Subconscious-ai/subconscious-ai-mcp.git
cd subconscious-ai-mcp

# Create virtual environment
python3 -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Set environment variables
export AUTH0_JWT_TOKEN="your_token_here"
export API_BASE_URL="https://api.subconscious.ai"

Add to your MCP config:

{
  "mcpServers": {
    "subconscious-ai": {
      "command": "/absolute/path/to/venv/bin/python3",
      "args": ["/absolute/path/to/server/main.py"],
      "env": {
        "AUTH0_JWT_TOKEN": "your_token",
        "API_BASE_URL": "https://api.subconscious.ai"
      }
    }
  }
}

📋 Available Tools

Tool Description
check_causality Validate that a research question is causal
generate_attributes_levels Generate experiment attributes and levels using AI
validate_population Validate target population demographics
get_population_stats Get population statistics for a country
create_experiment Create and run a conjoint experiment
get_experiment_status Check experiment progress
list_experiments List all your experiments
get_experiment_results Get detailed experiment results
get_run_details Get detailed run information
get_run_artifacts Get run artifacts and files
update_run_config Update run configuration
generate_personas Generate AI personas for an experiment
get_experiment_personas Get personas for an experiment
get_amce_data Get AMCE analytics data
get_causal_insights Get AI-generated causal insights

🔬 Example Workflow

You: "Check if this is a causal question: What factors influence people's decision to buy electric vehicles?"

AI: ✅ This is a causal question. Let me generate attributes for this study.

You: "Generate attributes for an EV preference study"

AI: Generated 5 attributes with 4 levels each:
    - Price: $25,000 / $35,000 / $45,000 / $55,000
    - Range: 200 miles / 300 miles / 400 miles / 500 miles
    ...

You: "Create an experiment about EV purchasing decisions"

AI: 🚀 Experiment created! Run ID: abc-123-xyz
    Status: Processing (surveying 500 synthetic respondents)

You: "Check the status of experiment abc-123-xyz"

AI: ✅ Experiment completed!
    - 500 respondents surveyed
    - Ready for analysis

You: "Get causal insights from this experiment"

AI: 📊 Key Findings:
    - Price has the strongest effect (-0.32 AMCE)
    - 400+ mile range increases preference by 28%
    - Brand reputation matters more than charging speed

🌐 REST API

Call tools directly via HTTP for integrations:

# List experiments
curl -X POST https://ghostshell-runi.vercel.app/api/call/list_experiments \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"limit": 5}'

# Check causality
curl -X POST https://ghostshell-runi.vercel.app/api/call/check_causality \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"why_prompt": "What factors influence EV purchases?"}'

# Create experiment
curl -X POST https://ghostshell-runi.vercel.app/api/call/create_experiment \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"why_prompt": "What factors influence EV purchases?", "confidence_level": "Reasonable"}'

# Get experiment results
curl -X POST https://ghostshell-runi.vercel.app/api/call/get_experiment_results \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"run_id": "your-run-id"}'

📡 API Endpoints

Endpoint Method Auth Description
/ GET No Server info and available tools
/api/health GET No Health check
/api/tools GET No List all tools with schemas
/api/sse GET Yes MCP SSE connection (token in query param)
/api/call/{tool} POST Yes Call a tool directly

🏗️ Self-Hosting on Vercel

Deploy your own instance for your organization:

# Install Vercel CLI
npm i -g vercel

# Clone and deploy
git clone https://github.com/Subconscious-ai/subconscious-ai-mcp.git
cd subconscious-ai-mcp
vercel --prod

Configure environment variables in Vercel dashboard:

  • API_BASE_URL: https://api.subconscious.ai (or your backend URL)

⚠️ Users must provide their own tokens - the server proxies requests to the Subconscious AI backend.

💡 Feature Requests & Support

Have a feature request or need help? Email us at nihar@subconscious.ai

📚 Resources

📄 License

This software requires an active Subconscious AI subscription. See the LICENSE file for details.


<p align="center"> Made with ❤️ by <a href="https://subconscious.ai">Subconscious AI</a> </p>

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