Linkedin.Mcp 1.0.3

LinkedIn MCP Server

A Model Context Protocol (MCP) server for fetching LinkedIn profiles via the Apify LinkedIn Profile Scraper API. Returns profile data in YAML format.

Prerequisites

• .NET 9.0 or later
• An Apify API token (Get one here)

Installation

Install the tool globally using dotnet:

dotnet tool install --global Linkedin.Mcp

Configuration

1. Set up your Apify API token

The tool requires the APIFY_TOKEN environment variable to be set.

Windows (PowerShell):

$env:APIFY_TOKEN = "your-apify-token-here"
# To persist across sessions:
[System.Environment]::SetEnvironmentVariable('APIFY_TOKEN', 'your-apify-token-here', 'User')

Linux/macOS:

export APIFY_TOKEN=your-apify-token-here
# To persist, add to ~/.bashrc or ~/.zshrc:
echo 'export APIFY_TOKEN=your-apify-token-here' >> ~/.bashrc

2. Configure Claude Code

Add the MCP server to your Claude Code configuration file.

Location:

• Windows: %APPDATA%\Claude\claude_desktop_config.json
• macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
• Linux: ~/.config/Claude/claude_desktop_config.json

Configuration:

{
  "mcpServers": {
    "linkedin": {
      "command": "linkedin-mcp",
      "env": {
        "APIFY_TOKEN": "your-apify-token-here"
      }
    }
  }
}

Alternatively, if you've set the environment variable globally, you can omit the env section:

{
  "mcpServers": {
    "linkedin": {
      "command": "linkedin-mcp"
    }
  }
}

Usage in Claude Code

Once configured, restart Claude Code. The LinkedIn MCP server will be available with the following tool:

fetch-profile

Fetches a LinkedIn profile and returns it in YAML format.

Parameters:

• profile_url (required): The LinkedIn profile URL
• include (optional): Array of optional sections to include in the output. If not specified, all sections are included.

Available optional sections:

• experiences - Work experience history
• updates - Recent activity and posts
• profilePicAllDimensions - All profile picture dimensions
• skills - Skills and endorsements
• educations - Educational background
• licenseAndCertificates - Professional certifications
• honorsAndAwards - Honors and awards
• languages - Language proficiencies
• volunteerAndAwards - Volunteer work
• verifications - Profile verifications
• promos - Promotional content
• highlights - Profile highlights
• projects - Projects
• publications - Publications
• patents - Patents
• courses - Courses
• testScores - Test scores
• organizations - Organizations
• volunteerCauses - Volunteer causes
• interests - Interests
• recommendations - Recommendations

Note: Basic profile fields (name, headline, location, summary, etc.) are always included regardless of the include parameter.

Example prompts:

• "Fetch the LinkedIn profile for https://www.linkedin.com/in/username"
• "Get me the profile information for this LinkedIn URL: https://www.linkedin.com/in/username"
• "Show me the work experience from https://www.linkedin.com/in/username"
• "Fetch the profile but only include experiences and skills sections"
• "Get the profile with just educations and certifications"

Supported URL formats:

• https://www.linkedin.com/in/username
• https://linkedin.com/in/username
• http://www.linkedin.com/in/username
• linkedin.com/in/username

Output Format

The tool returns LinkedIn profile data in YAML format.

Always included fields:

• Personal Information: Name, headline, location, profile picture
• Professional Summary: About/summary section
• Contact Information: LinkedIn URL, public identifier

Optional sections (included by default, can be filtered with the include parameter):

• Work Experience: Job titles, companies, dates, descriptions
• Education: Schools, degrees, fields of study
• Skills: List of professional skills and endorsements
• Certifications: Professional certifications and licenses
• Languages: Language proficiencies
• Projects: Personal and professional projects
• Publications: Published works
• Patents: Patent information
• And more: Updates, honors, awards, recommendations, etc.

Use the include parameter to fetch only the sections you need, reducing response size and processing time.