LinkedIn Automation MCP Server

An MCP (Model Context Protocol) server for LinkedIn automation that provides tools for automatically posting messages to LinkedIn, scheduling posts, and managing LinkedIn API integration.

Features

• Authentication: OAuth2 authentication with LinkedIn API
• Text Posts: Create and publish text posts to LinkedIn
• Image Posts: Upload and post images with text content
• Post Scheduling: Schedule posts to be published at specific times
• Profile Management: Get authenticated user's LinkedIn profile information
• Scheduled Post Management: View, cancel, and manage scheduled posts

Installation

1. Clone this repository
2. Install dependencies:

   npm install
   

3. Build the project:

   npm run build
   

Configuration

Before using this MCP server, you need to:

1. Create a LinkedIn App:

   • Go to LinkedIn Developer Portal
   • Create a new app and get your Client ID and Client Secret
   • Configure OAuth redirect URLs

2. Get an Access Token:

   • Implement OAuth2 flow to get an access token
   • The access token needs the following scopes:
     • r_liteprofile (read profile information)
     • r_emailaddress (read email address)
     • w_member_social (write posts)

Tools Available

authenticate_linkedin

Authenticate with LinkedIn using an OAuth2 access token.

Parameters:

• accessToken (string): LinkedIn OAuth2 access token

post_to_linkedin

Post a text message to LinkedIn.

Parameters:

• text (string): The text content of the post (1-3000 characters)
• visibility (string): Post visibility - "PUBLIC", "CONNECTIONS", or "LOGGED_IN_MEMBERS" (default: "PUBLIC")

post_image_to_linkedin

Post an image with text to LinkedIn.

Parameters:

• text (string): The text content of the post (1-3000 characters)
• imageUrl (string): URL of the image to include in the post
• altText (string, optional): Alternative text for the image
• visibility (string): Post visibility - "PUBLIC", "CONNECTIONS", or "LOGGED_IN_MEMBERS" (default: "PUBLIC")

schedule_linkedin_post

Schedule a post to be published later on LinkedIn.

Parameters:

• text (string): The text content of the post (1-3000 characters)
• scheduledTime (string): ISO 8601 timestamp for when to publish the post
• visibility (string): Post visibility - "PUBLIC", "CONNECTIONS", or "LOGGED_IN_MEMBERS" (default: "PUBLIC")

get_linkedin_profile

Get the authenticated user's LinkedIn profile information.

Parameters: None

get_scheduled_posts

Get all scheduled posts.

Parameters: None

cancel_scheduled_post

Cancel a scheduled post.

Parameters:

• scheduleId (string): The ID of the scheduled post to cancel

Usage with Claude Desktop

1. Build the server:

   npm run build
   

2. Add to Claude Desktop configuration (claude_desktop_config.json):

   {
     "mcpServers": {
       "linkedin-automation": {
         "command": "node",
         "args": ["/absolute/path/to/linkedin-automation-mcp/build/index.js"]
       }
     }
   }
   

3. Restart Claude Desktop

Development

# Install dependencies
npm install

# Build the project
npm run build

# Run the server (for testing)
npm start

# Development mode (build and run)
npm run dev

LinkedIn API Rate Limits

This server respects LinkedIn API rate limits:

• Rate limit information is tracked and logged
• Automatic retry with backoff for rate-limited requests
• Best practices for API usage

Security Considerations

• Access Tokens: Never commit access tokens to version control
• Scopes: Only request necessary OAuth scopes
• Rate Limiting: Respect LinkedIn's API rate limits
• Error Handling: Proper error handling for API failures

Error Handling

The server includes comprehensive error handling for:

• Authentication failures
• API rate limits
• Network errors
• Invalid parameters
• LinkedIn API errors

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests if applicable
5. Submit a pull request

License

MIT License - see LICENSE file for details

Support

For issues and questions:

1. Check the LinkedIn Developer Documentation
2. Review the MCP documentation at https://modelcontextprotocol.io/
3. Create an issue in this repository

Disclaimer

This project is not officially affiliated with LinkedIn. Use in accordance with LinkedIn's API Terms of Service and Community Guidelines.