linkedin-automation-mcp 0.0.2

A LinkedIn scraping and automation tool

LinkedIn Automation MCP

A Model Context Protocol (MCP) server that provides LinkedIn automation and scraping functionality. This package allows you to automate various LinkedIn tasks including profile scraping, post creation, and connection management.

Features

• Scrape LinkedIn Posts: Retrieve recent posts from specified LinkedIn profiles
• Send LinkedIn Connection Requests: Find profiles based on a search query and send connection requests, optionally including a personalized note
• Get Profile Information: Obtain basic information about specific LinkedIn profiles
• Post Content to LinkedIn: Create and post new content on LinkedIn on behalf of the user
• Combine all these to automate a lot of linkedin tasks together

Components

Prompts

The server provides several prompts for different LinkedIn automation tasks:

• scrape_content_and_post_to_linkedin: Scrape content and create LinkedIn posts
• research_and_create_linkedin_post: Research topics and generate posts
• post_to_linkedin: Publish content to LinkedIn
• get_profile_info: Extract LinkedIn profile information
• scrape_posts: Collect posts from LinkedIn
• send_connection_requests: Manage connection requests
• generate_post: Create engaging LinkedIn content

Tools

The package implements various tools in the tools directory:

• LinkedIn automation utilities
• Browser interaction helpers
• Content generation tools
• Data models for structured information

Installation

Requires UV (Fast Python package and project manager)

If UV isn't installed:

# Using Homebrew on macOS 
brew install uv

# On macOS and Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# On Windows
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Install the package:

# Install from PyPI
uv pip install linkedin-automation-mcp

# Install from source
uv pip install git+https://github.com/shahshrey/linkedin-automation.git

Claude Desktop

Add this tool as a mcp server by editing the Claude config file.

The config file location depends on your operating system:

• MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Windows: %APPDATA%/Claude/claude_desktop_config.json

{
  "linkedin-automation": {
    "command": "uv",
    "args": ["run", "linkedin-automation-mcp"],
    "env": {
      "LINKEDIN_EMAIL": "[e-mail]",
      "LINKEDIN_PASSWORD": "your_password"
    }
  }
}

To verify the server is working. Open the Claude client and use a prompt like "search about RAG, write a post on it in my style and post it on my linkedin". You should see an alert box open to confirm tool usage. Click "Allow for this chat"

Development

1. Clone the repository
2. Install dependencies:

uv pip install -e .

3. Run tests:

pytest

Contributing

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