About
Integrates with LinkedIn to enable automated profile browsing, searching, and post interactions using Playwright for browser automation and secure session management.
Details
- Author
- alinaqi
- Repository
- alinaqi/mcp-linkedin-server
- GitHub stars
- 18
- Categories
- Productivity, Developer Tools, Design, File Management, AI, Community, Media, Search, Infrastructure, Project Management, Automation, Frontend
Jump to
- 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
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
LinkedInCommand (node, npx, python, etc.)npxArguments-
Argument 1
-y -
Argument 2
@highlight/mcp-server
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
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
```python
from fastmcp import FastMCP
login_linkedin_secure
Securely log in using environment credentials.
browse_linkedin_feed
Browse and extract posts from the LinkedIn feed.
search_linkedin_profiles
Search for profiles matching specified criteria.
view_linkedin_profile
View and extract data from specific LinkedIn profiles.
interact_with_linkedin_post
Like, comment on, or read content from LinkedIn posts.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"linkedin": {
"env": {},
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}
}
}Linux
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}Macos
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}Windows
{
"env": [],
"args": [
"/c",
"npx",
"-y",
"@highlight/mcp-server"
],
"command": "cmd"
}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:
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
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
```python
from fastmcp import FastMCP
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