mcp-subconscios

mcp-subconscios

Run conjoint experiments and causal research through AI powered behavioral simulations

Category
Visit Server

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>

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured