MCP.so
Sign In

MCP Server for LinkedIn

@Hritik003

About MCP Server for LinkedIn

A MCP server for LinkedIn to seamlessly apply for jobs🚀

Basic information

Category

Other

Runtime

python

Transports

stdio

Publisher

Hritik003

Config

No standard config provided

This server doesn't expose a parseable MCP config block in its README. See the repository for install instructions.

Repository

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is MCP Server for LinkedIn?

MCP Server for LinkedIn is a Model Context Protocol server that enables programmatic job applications and feed browsing on LinkedIn. It leverages the unofficial LinkedIn API documentation to interact with LinkedIn using a user’s credentials. This server is intended for developers and automation enthusiasts who want to integrate LinkedIn actions into MCP-enabled workflows.

How to use MCP Server for LinkedIn?

Clone the repository and configure the local path in the JSON configuration. The server runs via uv with a specified local directory. Testing was performed using the mcp-cli client.

Key features of MCP Server for LinkedIn

  • Fetch user profiles via get_profile() (name, headline, current position)
  • Advanced job search with filters (keywords, location, experience level, job type, remote options, date posted, required skills)
  • Retrieve feed posts with configurable limit and offset for pagination
  • Parse PDF resumes to extract name, email, phone, skills, work experience, education, and languages

Use cases of MCP Server for LinkedIn

  • Automate job applications based on custom criteria
  • Extract and analyze LinkedIn profiles for networking or recruitment
  • Search jobs with multiple filters and apply programmatically
  • Parse candidate resumes and match them to job requirements
  • Monitor LinkedIn feed within an MCP-driven agent loop

FAQ from MCP Server for LinkedIn

What does it integrate with?

It integrates with LinkedIn via the unofficial LinkedIn API.

What are the runtime requirements?

It requires uv and Python. The server is launched as a command using uv and a local folder.

Where does my data live?

Data is fetched from LinkedIn’s API and processed locally. The README does not mention any external storage or cloud persistence.

Is authentication required?

Yes, client credentials are used to hit the unofficial LinkedIn API endpoints.

What limitations does it have?

It uses an unofficial API, so reliability may change. Resume parsing supports only PDF format.

Comments

More Other MCP servers