LinkedIn Browser MCP Server

A FastMCP-based server for LinkedIn automation and data extraction using browser automation. This server provides a set of tools for interacting with LinkedIn programmatically while respecting LinkedIn's terms of service and rate limits.

Features

Secure Authentication
- Environment-based credential management
- Session persistence with encrypted cookie storage
- Rate limiting protection
- Automatic session recovery
Profile Operations
- View and extract profile information
- Search for profiles based on keywords
- Browse LinkedIn feed
- Profile visiting capabilities
Post Interactions
- Like posts
- Comment on posts
- Read post content and engagement metrics

Prerequisites

Python 3.8+
Playwright
FastMCP library
LinkedIn account

Installation

Clone the repository:

git clone [repository-url]
cd mcp-linkedin-server

Create and activate a virtual environment:

python -m venv env
source env/bin/activate  # On Windows: env\Scripts\activate

Install dependencies:

pip install -r requirements.txt
playwright install chromium

Set up environment variables: Create a .env file in the root directory with:

LINKEDIN_USERNAME=your_email@example.com
LINKEDIN_PASSWORD=your_password
COOKIE_ENCRYPTION_KEY=your_encryption_key  # Optional: will be auto-generated if not provided

Usage

Start the MCP server:

python linkedin_browser_mcp.py

Available Tools:

login_linkedin_secure: Securely log in using environment credentials
browse_linkedin_feed: Browse and extract posts from feed
search_linkedin_profiles: Search for profiles matching criteria
view_linkedin_profile: View and extract data from specific profiles
interact_with_linkedin_post: Like, comment, or read posts

Example Usage

from fastmcp import FastMCP

# Initialize client
client = FastMCP.connect("http://localhost:8000")

# Login
result = await client.login_linkedin_secure()
print(result)

# Search profiles
profiles = await client.search_linkedin_profiles(
    query="software engineer",
    count=5
)
print(profiles)

# View profile
profile_data = await client.view_linkedin_profile(
    profile_url="https://www.linkedin.com/in/username"
)
print(profile_data)

Security Features

Encrypted cookie storage
Rate limiting protection
Secure credential management
Session persistence
Browser automation security measures

Best Practices

Rate Limiting: The server implements rate limiting to prevent excessive requests:
- Maximum 5 login attempts per hour
- Automatic session reuse
- Cookie persistence to minimize login needs
Error Handling: Comprehensive error handling for:
- Network issues
- Authentication failures
- LinkedIn security challenges
- Invalid URLs or parameters
Session Management:
- Automatic cookie encryption
- Session persistence
- Secure storage practices

Contributing

Fork the repository
Create a feature branch
Commit your changes
Push to the branch
Create a Pull Request

License

MIT

Disclaimer

This tool is for educational purposes only. Ensure compliance with LinkedIn's terms of service and rate limiting guidelines when using this software.