LinkedIn Model Context Protocol (MCP) Server

A powerful Model Context Protocol server for LinkedIn interactions that enables AI assistants to search for jobs, generate resumes and cover letters, and manage job applications programmatically.

Features

• Authentication: Secure LinkedIn authentication with session management
• Profile Management: Access and update LinkedIn profile information
• Job Search: Search for jobs with flexible filtering options
• Resume Generation: Create customized resumes from LinkedIn profiles
• Cover Letter Generation: Generate tailored cover letters for specific job applications
• Job Applications: Submit and track job applications

Architecture

This project implements the Model Context Protocol (MCP) specification, allowing AI assistants to interact with LinkedIn through standardized JSON-RPC style requests and responses.

Components:

• MCP Handler: Routes requests to appropriate service handlers
• API Modules: Specialized modules for LinkedIn interactions (auth, job search, profile, etc.)
• Core Protocol: Defines request/response structures and data models
• Utilities: Configuration management and helper functions

Installation

# Clone the repository
git clone https://github.com/yourusername/linkedin-mcp.git
cd linkedin-mcp

# Create and activate a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

Configuration

Create a .env file in the project root with the following variables:

# LinkedIn Credentials
[email protected]
LINKEDIN_PASSWORD=your_password

# API Settings
OPENAI_API_KEY=your_openai_api_key
SESSION_DIR=sessions
DATA_DIR=data

Usage

Starting the Server

python server.py

Example MCP Requests

Authentication

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "linkedin.login",
  "params": {
    "username": "[email protected]",
    "password": "password123"
  }
}

Searching for Jobs

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "linkedin.searchJobs",
  "params": {
    "filter": {
      "keywords": "software engineer",
      "location": "New York, NY",
      "distance": 25
    },
    "page": 1,
    "count": 20
  }
}

Generating a Resume

{
  "jsonrpc": "2.0",
  "id": 3,
  "method": "linkedin.generateResume",
  "params": {
    "profileId": "user123",
    "template": "standard",
    "format": "pdf"
  }
}

Available Methods

Method	Description
linkedin.login	Authenticate with LinkedIn
linkedin.logout	End the current session
linkedin.checkSession	Check if the current session is valid
linkedin.getFeed	Get LinkedIn feed posts
linkedin.getProfile	Get LinkedIn profile information
linkedin.getCompany	Get company profile information
linkedin.searchJobs	Search for jobs with filters
linkedin.getJobDetails	Get detailed information about a job
linkedin.getRecommendedJobs	Get job recommendations
linkedin.generateResume	Generate a resume from a LinkedIn profile
linkedin.generateCoverLetter	Generate a cover letter for a job application
linkedin.tailorResume	Customize a resume for a specific job
linkedin.applyToJob	Apply to a job
linkedin.getApplicationStatus	Check application status
linkedin.getSavedJobs	Get saved jobs
linkedin.saveJob	Save a job for later

Development

Project Structure

linkedin-mcp/
├── README.md
├── requirements.txt
├── server.py
├── data/
│   ├── applications/
│   ├── companies/
│   ├── cover_letters/
│   ├── jobs/
│   ├── profiles/
│   └── resumes/
├── linkedin_mcp/
│   ├── api/
│   │   ├── auth.py
│   │   ├── cover_letter_generator.py
│   │   ├── job_application.py
│   │   ├── job_search.py
│   │   ├── profile.py
│   │   └── resume_generator.py
│   ├── core/
│   │   ├── mcp_handler.py
│   │   └── protocol.py
│   └── utils/
│       └── config.py
├── sessions/
└── templates/
    ├── cover_letter/
    │   └── standard.html
    └── resume/
        └── standard.html

Running Tests

pytest

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• LinkedIn API documentation
• Model Context Protocol specification