LinkedIn MCP Server
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@LinkedIn MCP ServerFind remote software engineering jobs in San Francisco"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Profile Retrieval
Fetch user profiles using
get_profile()function Extract key information such asname,headline, andcurrent positionJob 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
Feed Posts
Retrieve LinkedIn feed posts using
get_feed_posts()Configurable limit and offset for pagination
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 repo, adjust the <LOCAL_PATH> accordingly
{
"linkedin":{
"command":"uv",
"args": [
"--directory",
"<LOCAL_PATH>",
"run",
"linkedin.py"
]
}
}
Usage
I have been testing using MCP-client and found as the best one for testing your MCP-Servers.
This server cannot be deployed
Maintenance
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LinkedIn for AI agents: inbox, invitations, Sales Navigator search, posts. Quotas and webhooks.
Give AI agents the LinkedIn tools to find, qualify, engage, and follow up with prospects.
Live LinkedIn data for AI agents: profiles, companies, jobs, posts, email finding. No account risk.
Query professional profiles, search candidates, and get AI-powered summaries and job fit analysis.
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