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YouTube Sponsorship Workflow - Gmail-Powered Kanban Board

A modern kanban board application for managing YouTube sponsorship deals, powered directly by Gmail API. Built with Next.js 15, TypeScript, and shadcn/ui components.

🚨 Gmail Connection Setup Required

The "NetworkError when attempting to fetch resource" error occurs because Google OAuth credentials are not configured.

Quick Fix:

  1. Set up Google OAuth credentials (see GMAIL_OAUTH_SETUP.md)
  2. Update .env.local with your actual credentials
  3. Restart the development server

For detailed setup instructions, see:

🚀 Features

Gmail Integration

  • Direct Gmail API Access: No backend required - connects directly to Gmail
  • OAuth Authentication: Secure Google OAuth 2.0 authentication
  • Real-time Email Data: Always shows current Gmail state
  • Label Filtering: Organize emails by Gmail labels
  • No Mock Data: Uses real Gmail data exclusively - see Using Real Gmail Data

Dashboard Views

  • Gmail View: Browse and filter emails directly from Gmail
  • Kanban View: Traditional kanban board for workflow management
  • Toggle Between Views: Easy switching between Gmail and Kanban views

Deal Management (Kanban View)

  • 9-Stage Workflow:
    • Prospecting
    • Initial Contact
    • Negotiation
    • Contract Sent
    • Contract Signed
    • Content Creation
    • Content Review
    • Published
    • Completed
  • Drag & Drop: Move deals between stages
  • Deal Details: Track value, contacts, notes, and attachments
  • Bulk Operations: Select and move/delete multiple deals

📋 Prerequisites

  • Node.js 18+ and npm
  • Google account
  • Google Cloud Console access (free)

🛠️ Installation

  1. Clone the repository

    git clone <repository-url>
    cd kanban-app
  2. Install dependencies

    npm install
  3. Set up environment variables

    cp .env.example .env.local
  4. Configure Google OAuth (see GMAIL_OAUTH_SETUP.md)

  5. Run the development server

    npm run dev
  6. Open the application

📚 Documentation

🤝 Contributing

Contributions are welcome! Please read our contributing guidelines before submitting PRs.

📄 License

This project is licensed under the MIT License.

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