AI Knowledge System

An enterprise-ready system to archive AI conversations from ChatGPT and Claude into a Supabase database.

GitHub

🧠 AI Knowledge System

Enterprise-Ready Conversation Archive for ChatGPT + Claude

Transform your AI conversations from lost chat history into a searchable, organized knowledge base. This system captures insights from both ChatGPT Enterprise and Claude Desktop, storing everything in a structured database for long-term reference and analysis.

✨ Features

  • 🔄 Dual AI Integration: Seamlessly capture conversations from both ChatGPT and Claude
  • 🏢 Enterprise Compliant: Works with ChatGPT Enterprise restrictions via browser extension
  • 📊 Smart Organization: Auto-categorize by strategy, user feedback, competitive analysis, etc.
  • 🎯 Priority Levels: Mark conversations as low, medium, high, or critical importance
  • 📅 Time-Based Filtering: Automatic quarterly tagging for periodic reviews
  • 🔍 Powerful Search: Query across months of conversations to find patterns and insights
  • 🛡️ Privacy First: Your data stays in your own Supabase database
  • ⚡ One-Click Save: Browser extension makes saving ChatGPT conversations effortless

🎯 Perfect For

  • Product Managers building competitive intelligence and user research repositories
  • Consultants maintaining client insight databases
  • Researchers organizing AI-assisted analysis sessions
  • Teams creating shared knowledge bases from AI conversations
  • Anyone who wants to stop losing valuable AI insights

🚀 Quick Start

Prerequisites

  • Node.js 18+
  • Chrome browser
  • Supabase account (free tier works)

1. Database Setup

-- Create your conversations table
CREATE TABLE conversations (
  id SERIAL PRIMARY KEY,
  topic VARCHAR(100),
  content TEXT NOT NULL,
  category VARCHAR(50),
  priority VARCHAR(10),
  source VARCHAR(20),
  tags TEXT[],
  conversation_date DATE DEFAULT CURRENT_DATE,
  quarter VARCHAR(10),
  created_at TIMESTAMP DEFAULT NOW()
);

2. API Deployment

Deploy to Render

git clone https://github.com/yourusername/ai-knowledge-system
cd ai-knowledge-system/api-server
npm install
npm start

Set environment variables:

  • SUPABASE_URL
  • SUPABASE_ANON_KEY

3. Browser Extension Setup

  1. Open chrome://extensions/
  2. Enable "Developer mode"
  3. Click "Load unpacked"
  4. Select the browser-extension folder

4. Claude Desktop Integration

Add to ~/.claude/claude_desktop_config.json:

{
  "mcpServers": {
    "supabase": {
      "command": "node",
      "args": ["/path/to/supabase-mcp/packages/mcp-server-supabase/dist/transports/stdio.js"],
      "env": {
        "SUPABASE_ACCESS_TOKEN": "your_token",
        "SUPABASE_URL": "your_url",
        "SUPABASE_ANON_KEY": "your_key",
        "SUPABASE_PROJECT_REF": "your_project"
      }
    }
  }
}

💡 Usage Examples

ChatGPT Enterprise

  1. Have your conversation normally
  2. Click the extension icon
  3. Review auto-suggested topic
  4. Select category and priority
  5. Click "Save Conversation"

Claude Desktop

"Save this strategy conversation with high priority: 
[your conversation content]"

"Show me all user feedback insights from Q1 2025"

"Find high-priority competitive analysis discussions"

🏗️ Architecture

ChatGPT Enterprise → Browser Extension → API Server → Supabase
Claude Desktop → MCP Protocol → Local Server → Supabase

Components

  • Browser Extension: Captures ChatGPT conversations with enterprise compliance
  • API Server: Hosted endpoint for saving conversations to database
  • MCP Integration: Direct Claude Desktop to database connection
  • Supabase Database: PostgreSQL with structured conversation storage

📁 Project Structure

ai-knowledge-system/
├── browser-extension/
│   ├── manifest.json
│   ├── popup.html
│   ├── popup.js
│   └── content.js
├── api-server/
│   ├── server.js
│   ├── package.json
│   └── .env.example
├── mcp-setup/
│   └── claude_desktop_config.json
├── database/
│   └── schema.sql
└── docs/
    └── technical-overview.html

🔧 Configuration

Categories

  • strategy - High-level planning and direction
  • user_feedback - Customer insights and research
  • competitive_analysis - Market and competitor research
  • brainstorming - Creative ideation sessions
  • general - Miscellaneous conversations

Priority Levels

  • critical - Mission-critical insights
  • high - Important for near-term decisions
  • medium - Useful reference material
  • low - Nice-to-have information

🛠️ Development

Local Development

# API Server
cd api-server
npm install
npm run dev

# Extension Development
# Load unpacked extension in Chrome for hot reloading

Adding Features

  • New Categories: Update database constraints and extension dropdown
  • Custom Fields: Extend database schema and forms
  • Integrations: Add new AI tools following the extension pattern

🤝 Contributing

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

📋 Roadmap

  • Slack integration for team sharing
  • Export to PDF/Word reports
  • Advanced analytics dashboard
  • Mobile app for conversation capture
  • Integration with Notion/Obsidian
  • Multi-user support with permissions

⚠️ Enterprise Considerations

This system is designed to work within enterprise constraints:

  • ✅ No API keys required for ChatGPT Enterprise
  • ✅ Data stays in your own database
  • ✅ Browser extension uses standard web APIs
  • ✅ No external AI service dependencies

📄 License

MIT License - see LICENSE file for details.

🙏 Acknowledgments

📧 Support

Built by product managers, for product managers. 🚀

Stop losing your best AI insights. Start building your knowledge advantage.

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