What is Mcp Linkedin Server

The mcp-linkedin-server is a FastMCP-based server designed for automating interactions with LinkedIn and extracting data through browser automation, while adhering to LinkedIn’s terms of service and rate limits.

Use cases

Use cases for the mcp-linkedin-server include automating profile searches for recruitment, extracting data for market research, managing LinkedIn interactions for personal branding, and analyzing engagement metrics on posts.

How to use

To use the mcp-linkedin-server, clone the repository, set up a virtual environment, install the required dependencies, configure your LinkedIn credentials in a .env file, and start the server. You can then utilize various tools provided by the server for secure login, profile searches, and post interactions.

Key features

Key features include secure authentication with environment-based credential management, session persistence with encrypted cookie storage, profile operations such as viewing and extracting profile information, and post interactions like liking and commenting on posts.

Where to use

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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

1. Clone the repository:

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

2. Create and activate a virtual environment:

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

3. Install dependencies:

pip install -r requirements.txt
playwright install chromium

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

[email protected]
LINKEDIN_PASSWORD=your_password
COOKIE_ENCRYPTION_KEY=your_encryption_key  # Optional: will be auto-generated if not provided

Usage

1. Start the MCP server:

python linkedin_browser_mcp.py

2. 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

1. 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

2. Error Handling: Comprehensive error handling for:

   • Network issues
   • Authentication failures
   • LinkedIn security challenges
   • Invalid URLs or parameters

3. Session Management:

   • Automatic cookie encryption
   • Session persistence
   • Secure storage practices

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. 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.