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linkedin-mcp-server

by stickerdaniel3.4kPythonUpdated 2026-09-07

Open-source MCP server for LinkedIn. Give Claude and any MCP-compatible AI agent access to profiles, companies, jobs, and messages.

Claude DesktopCodex

linkedin-mcp-server is an open-source MCP server that connects AI assistants like Claude to LinkedIn through an authenticated browser session. It enables AI agents to look up profiles and companies, send messages, manage inboxes, and search for jobs—all running locally via browser automation. The server works with any MCP-compatible client and uses Patchright Chromium to interact with LinkedIn as if you were browsing manually. Developers install it via uvx, Docker, or as a Claude Desktop MCP Bundle, authenticate once with their LinkedIn account, and then give their AI assistant direct access to LinkedIn data and messaging.

Key Features

Retrieve LinkedIn profile information with granular section selection (experience, education, skills, posts, contact info)
Search for people by keywords, location, connection degree, and current company filters
Send and read LinkedIn messages, search conversations, and manage inbox threads
Extract company profiles, posts, employee lists, and search for companies by keyword
Search and retrieve job postings with location filters, plus access saved jobs
Browser session auto-import from locally signed-in Chrome, Brave, Edge, and other Chromium browsers
Shared browser process with serialized tool calls to support multiple MCP clients simultaneously
Docker support with web-based login viewer and proxy configuration for VPS/remote deployments

Use Cases

  • 01Automate LinkedIn research by having Claude gather profile data and company information for prospect lists
  • 02Monitor job postings and save relevant opportunities through AI-driven search queries
  • 03Manage LinkedIn messaging at scale by delegating inbox triage and message composition to an AI assistant
  • 04Extract employee lists and organizational data for market research or recruiting workflows
  • 05Build AI agents that combine LinkedIn data with other sources for comprehensive business intelligence
  • 06Automate connection requests and follow-up messaging based on profile criteria

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linkedin-mcp-server — FAQ

What is linkedin-mcp-server?+

It's an MCP server that connects AI assistants like Claude to LinkedIn through your own authenticated browser session, enabling profile lookups, messaging, job searches, and company research via local browser automation.

How do I install linkedin-mcp-server with Claude Desktop?+

Install uv, then add the server to Claude Desktop's config with the command 'uvx mcp-server-linkedin@latest'. On first use, authenticate by signing into LinkedIn in the browser window that opens automatically.

Which AI clients work with this MCP server?+

Any MCP-compatible client works, including Claude Desktop, and it also supports Codex as a plugin. The server runs in stdio mode for local clients or streamable HTTP mode for web-based integrations.

Do I need a LinkedIn API key or special account?+

No API key is needed—just your regular LinkedIn account credentials. You authenticate once through a browser login, and the server saves your session locally for subsequent tool calls.

Is linkedin-mcp-server free and open source?+

Yes, it's free and licensed under Apache 2.0. However, LinkedIn's terms prohibit automated access, so use at your own risk; accounts using automation tools can be restricted or banned.

Will using this get my LinkedIn account banned?+

LinkedIn's User Agreement prohibits automated access, and accounts using automation can face restrictions or bans. This tool uses real browser sessions rather than undocumented APIs, but there is no guarantee of account safety—use responsibly and at your own risk.

How do I install linkedin-mcp-server?+

Open the source repository on GitHub and follow its README. linkedin-mcp-server is a mcp server — MCP Agents Market links you directly to the official repo.

Is linkedin-mcp-server free?+

linkedin-mcp-server is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.

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