📌Overview

Purpose: To provide a Model Context Protocol (MCP) server that allows seamless job applications and feed searches on LinkedIn.

Overview: The MCP Server for LinkedIn enables users to access and utilize LinkedIn's functionalities such as profile retrieval, job search, and feed post retrieval through an unofficial API, streamlining the interaction with the platform.

Key Features:

• Profile Retrieval: Utilize the get_profile() function to fetch user profiles and extract essential details like name, headline, and current position.

• Job Search: Comprehensive job search capabilities that allow users to filter by keywords, location, experience level, job type, remote options, posting date, and required skills, with customizable search limits.

• Feed Posts: Access LinkedIn feed posts via the get_feed_posts() function, supporting pagination with configurable limits and offsets.

• Resume Analysis: Analyze and extract key information from resumes in PDF format, identifying details such as contact information, skills, work experience, education, and languages.

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MCP Server for LinkedIn

A Model Context Protocol (MCP) server for LinkedIn that allows seamless job applications and feed searches using the unofficial LinkedIn API documentation.

Features

1. Profile Retrieval

   • Fetch user profiles using get_profile() function
   • Extract key information such as name, headline, and current position

2. Job Search

   • Advanced job search with parameters:
     • Keywords
     • Location
     • Experience level
     • Job type (Full-time, Contract, Part-time)
     • Remote work options
     • Date posted
     • Required skills
   • Customizable search limit

3. Feed Posts

   • Retrieve LinkedIn feed posts using get_feed_posts()
   • Configurable limit and offset for pagination

4. Resume Analysis

   • Parse and extract information from resumes (PDF format)
   • Extracted data includes:
     • Name
     • Email
     • Phone number
     • Skills
     • Work experience
     • Education
     • Languages

Configuration

After cloning the repository, adjust the <LOCAL_PATH> accordingly:

{
    "linkedin": {
        "command": "uv",
        "args": [
            "--directory",
            "<LOCAL_PATH>",
            "run",
            "linkedin.py"
        ]
    }   
}

Usage

For testing the MCP server, the MCP-client is recommended.