eliasbiondo

eliasbiondo / linkedin-mcp-server

Public

🔗 A Model Context Protocol (MCP) server for LinkedIn — search people, companies, and jobs, scrape profiles, and get structured data via any MCP-compatible AI client.

59
4
69% credibility
Found Mar 10, 2026 at 20 stars 3x -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
Python
AI Summary

A local service that connects AI chat tools to LinkedIn, enabling searches for people, companies, jobs and extraction of structured profile data.

How It Works

1
🔍 Discover the LinkedIn Helper

You find a handy tool that lets your AI buddy search and pull info from LinkedIn profiles, companies, and jobs.

2
📥 Set it up on your computer

Download the tool and prepare it quickly so it's ready to use on your machine.

3
🖥️ Get the web viewer ready

Install a simple web viewer that mimics a real browser for visiting LinkedIn.

4
🔐 Sign into your LinkedIn

A browser window pops up – log into your LinkedIn account once, and it remembers your session safely.

5
▶️ Start the background helper

Turn on the service with a quick launch, and it runs quietly in the background.

6
🔗 Connect to your AI chat

Add a simple note to your AI tool's settings so it knows how to talk to the helper.

🎉 Get LinkedIn insights instantly

Now chat with your AI – ask for people, jobs, or company details, and receive neat, organized summaries right away!

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 20 to 59 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is linkedin-mcp-server?

This Python-based Model Context Protocol (MCP) server turns LinkedIn into a queryable database for AI clients like Claude Desktop or Cursor. Feed it searches for people, companies, or jobs with filters like date posted, remote/hybrid, or experience level, and it scrapes profiles into structured JSON—main details, experience, posts, contact info, and more. No custom scrapers needed; just authenticate once via browser and run it as a stdio or HTTP github model context protocol server.

Why is it gaining traction?

It stands out with granular tools like get_person_profile (pick sections like education or recommendations) and search_jobs (rich filters, extracts job IDs for details), all via model context protocol for seamless AI integration. Session cookies persist across runs, and it handles rate limits plus modals automatically—users get reliable data without babysitting a browser. Early adopters love the FastMCP backbone for quick setup in linkedin mcp server claude workflows.

Who should use this?

AI agent builders querying LinkedIn for lead gen or job matching. Devs in Claude/Cursor extending prompts with real-time profile data. Researchers needing structured company posts or people search results without building their own scrapers.

Verdict

Worth a spin for model context protocol fans—solid CLI like --login for auth, excellent docs, pre-commit, and pytest coverage make it dev-friendly despite 18 stars and 0.699999988079071% credibility score. Still early; test your use case as LinkedIn changes could break parsers, but it's a smart linkedin jobs mcp server starter.

(198 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.