About
Integrates with LinkedIn to enable profile retrieval, job searching, feed post access, and resume analysis for automated platform engagement.
Details
- Author
- hritik003
- Repository
- Hritik003/linkedin-mcp
- GitHub stars
- 24
- Downloads
- 8,964
- Categories
- Developer Tools, Design, File Management, AI, Search, Automation, Knowledge Base, API, Infrastructure, Other
Jump to
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 functionality with multiple 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
---
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
LinkedInCommand (node, npx, python, etc.)uvArguments-
Argument 1
--directory -
Argument 2
<LOCAL_PATH> -
Argument 3
run -
Argument 4
linkedin.py
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
I have been testing using MCP-client and found as the best one for testing your MCP-Servers.
get_profile
Fetch user profiles and extract key information such as name, headline, and current position.
job_search
Perform an advanced job search with parameters like keywords, location, experience level, job type, remote options, date posted, and required skills. Includes customizable search limit.
get_feed_posts
Retrieve LinkedIn feed posts with configurable limit and offset for pagination.
resume_analysis
Parse and extract information from resumes in PDF format, including name, email, phone number, skills, work experience, education, and languages.
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"linkedin": {
"cwd": "string (optional)",
"env": {},
"args": [
"--directory",
"<LOCAL_PATH>",
"run",
"linkedin.py"
],
"shell": false,
"command": "uv"
}
}
}Linux
{
"cwd": "string (optional)",
"env": [],
"args": [
"--directory",
"<LOCAL_PATH>",
"run",
"linkedin.py"
],
"shell": false,
"command": "uv"
}Macos
{
"cwd": "string (optional)",
"env": [],
"args": [
"--directory",
"<LOCAL_PATH>",
"run",
"linkedin.py"
],
"shell": false,
"command": "uv"
}Windows
{
"cwd": "string (optional)",
"env": [],
"args": [
"--directory",
"<LOCAL_PATH>",
"run",
"linkedin.py"
],
"shell": false,
"command": "uv"
}MCP Server for LinkedIn
A Model Context Protocol (MCP) server for linkedin to apply Jobs and search through feed seamlessly.
This uses Unoffical Linkedin API Docs for hitting at the clients Credentials.
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 functionality with multiple 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
---
Sign in to leave a review
Use Google, GitHub, or an email account so ratings stay tied to real people.
No reviews posted yet.
