🔗 Linkify

LinkedIn Connection Automation Tool

🌐 Live Demo • 📖 Documentation • 🐛 Report Bug • ✨ Request Feature

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📋 Table of Contents

• About
• Features
• Tech Stack
• Getting Started
• Usage
• Project Structure
• Deployment
• Security
• Contributing
• License
• Contact

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🎯 About

Linkify is a secure and efficient web-based tool designed to automate LinkedIn connection management. Built with Flask and Selenium, it provides a user-friendly interface for managing your professional network, automating the acceptance of connection requests while maintaining security and privacy.

Why Linkify?

• ⚡ Save Time: Automate repetitive connection management tasks
• 🔒 Stay Secure: Local session storage with no data collection
• 🎨 Modern UI: Clean, responsive interface that works on all devices
• 🚀 Easy Deploy: Ready for cloud deployment with one-click setup

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✨ Features

🔐 Authentication LinkedIn login with OTP support Session cookie persistence Secure credential handling Auto-relogin capability	🤖 Automation Batch accept connections Real-time progress tracking Smart scrolling mechanism Background processing
📊 Monitoring Live connection statistics Activity logging Request status tracking Visual progress indicators	🎨 User Experience Responsive mobile design Intuitive dashboard Clean, modern interface Fast load times

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🛠 Tech Stack

Category	Technology
Backend	Python 3.11+, Flask 2.3.2
Frontend	HTML5, CSS3, JavaScript
Automation	Selenium WebDriver 4.11.2
Deployment	Render Cloud Platform
Server	Gunicorn WSGI Server

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🚀 Getting Started

Prerequisites

• Python 3.11 or higher
• pip package manager

Setup Instructions

1. Clone the repository

   git clone https://github.com/mugenkyou/Linkify.git
   cd Linkify

2. Install dependencies

   pip install -r requirements.txt

3. Run the application

   python app.py

4. Access the application

   Open your browser and navigate to http://127.0.0.1:5000

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📖 Usage

Step-by-Step Guide

1. 🌐 Launch Application

   • Open your browser and navigate to the application URL

2. 🔑 Login to LinkedIn

   • Click on "Login" in the navigation
   • Enter your LinkedIn credentials
   • Complete OTP verification if prompted

3. 📊 View Dashboard

   • Access the connections dashboard
   • View your pending connection requests statistics

4. ⚡ Automate Connections

   • Click "Start Accepting" to begin automation
   • Watch real-time progress as connections are processed
   • Review completion statistics

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📁 Project Structure

Linkify/
├── 📄 app.py                  # Main Flask application
├── 📄 requirements.txt        # Python dependencies
├── 📄 render.yaml            # Render deployment configuration
├── 📁 static/                # Static assets
│   ├── css/                  # Stylesheets
│   ├── js/                   # JavaScript files
│   └── linkify-screenshot.png
├── 📁 templates/             # HTML templates
│   ├── base.html            # Base template
│   ├── index.html           # Landing page
│   ├── login.html           # Login page
│   ├── otp.html             # OTP verification
│   └── connections.html     # Dashboard
├── 📁 scripts/               # Utility scripts
│   ├── accept_connections.py
│   └── linkedin_login.py
└── 📁 cookies/               # Session storage (auto-generated)

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☁️ Deployment

Deploy to Render

The application is configured for one-click deployment on Render:

1. Fork this repository
2. Create a new Web Service on Render
3. Connect your GitHub repository
4. Render will automatically:
   • Detect the render.yaml configuration
   • Install dependencies from requirements.txt
   • Start the application with Gunicorn

Configuration

• Build Command: pip install -r requirements.txt
• Start Command: gunicorn app:app
• Python Version: 3.11.0
• Health Check: / endpoint

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🔒 Security & Privacy

Aspect	Implementation
Data Storage	Session cookies stored locally, no cloud database
Data Collection	Zero data collection - no analytics or tracking
Session Security	Secure session management with HTTP security headers
Credential Handling	Credentials used only for authentication, not stored
Privacy	All processing happens server-side, no third-party services

⚠️ Important Notes

• This tool is for educational purposes only
• Users must comply with LinkedIn's Terms of Service
• Excessive automation may result in account restrictions
• Use responsibly and within rate limits

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Contributing

Contributions are welcome! To contribute to this project:

1. Fork the repository
2. Create a feature branch

   git checkout -b feature/AmazingFeature

3. Commit your changes

   git commit -m 'Add some AmazingFeature'

4. Push to the branch

   git push origin feature/AmazingFeature

5. Open a Pull Request

Development Setup

# Create virtual environment
python -m venv venv

# Activate virtual environment
# On Windows:
venv\Scripts\activate
# On Unix/MacOS:
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Run development server
python app.py

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License

This project is licensed under the MIT License - see the LICENSE file for details.

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Author

Sachin Patel

• LinkedIn: linkedin.com/in/sachinskyte
• GitHub: github.com/mugenkyou

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Links

• Live Demo: https://linkify-mjyp.onrender.com/
• Repository: https://github.com/mugenkyou/Linkify
• Report Issues: https://github.com/mugenkyou/Linkify/issues

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Built with Flask and Selenium for secure LinkedIn automation