LinkedIn Browser
LinkedIn MCP Server for local automation
Installation
Installing for Claude Desktop
Manual Configuration Required
This MCP server requires manual configuration. Run the command below to open your configuration file:
npx mcpbar@latest edit -c claude
This will open your configuration file where you can add the LinkedIn Browser MCP server manually.
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:
[email protected]
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 credentialsbrowse_linkedin_feed
: Browse and extract posts from feedsearch_linkedin_profiles
: Search for profiles matching criteriaview_linkedin_profile
: View and extract data from specific profilesinteract_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.
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