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linkedin-mcp-server

stickerdaniel/linkedin-mcp-server

stickerdaniel

A Model Context Protocol (MCP) server that enables interaction with LinkedIn through AI assistants.

下载次数: 0状态:社区镜像维护者:stickerdaniel仓库类型:镜像最近更新:4 天前
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https://xuanyuan.cloud/agents.md

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MCP Server for LinkedIn

A Model Context Protocol (MCP) server that connects AI assistants to LinkedIn. Access profiles, companies, and job postings through a Docker container.

Disclaimer: This is an independent, community project. It is not affiliated with, authorized by, endorsed by, or sponsored by LinkedIn Corporation or Microsoft. "LinkedIn" is a registered trademark of LinkedIn Corporation and is used here only descriptively to identify the third-party service this software interoperates with.

Features

  • Profile Access: Get detailed LinkedIn profile information including experience, education, skills, projects, certifications, and more
  • Own Profile: Fetch the authenticated user's own profile to give agents self-context
  • Profile Connections: Send connection requests or accept incoming ones, with optional notes
  • Company Profiles: Extract comprehensive company data, including the LinkedIn company URN id (used by LinkedIn's people-search currentCompany URL facet)
  • Company Employees: List employees at a company with optional keyword filtering
  • Company Search: Search for companies by keyword
  • Job Details: Retrieve job posting information
  • Job Search: Search for jobs with keywords and location filters
  • People Search: Search for people by keywords and location
  • Person Posts: Get recent activity/posts from a person's profile
  • Company Posts: Get recent posts from a company's LinkedIn feed
  • Home Feed: Get recent posts from the authenticated user's LinkedIn home feed
  • Compact References: Return typed per-section links alongside readable text without shipping full-page markdown

Quick Start

Create a browser profile locally, then mount it into Docker. You still need uv installed on the host for the one-time uvx mcp-server-linkedin@latest --login step. Docker already includes its own Chromium runtime, so the managed Patchright Chromium browser download used by MCPB/uvx is not needed here.

Step 1: Create profile on the host (one-time setup)

bash
uvx mcp-server-linkedin@latest --login

This opens a browser window where you log in manually (5 minute timeout for 2FA, captcha, etc.). The browser profile and cookies are saved under ~/.linkedin-mcp/. On startup, Docker derives a Linux browser profile from your host cookies and creates a fresh session each time. For better stability, *** the https://github.com/stickerdaniel/linkedin-mcp-server#-uvx-setup-recommended---universal.

Already signed into LinkedIn in a browser on the host? Run uvx mcp-server-linkedin@latest --import-from-browser on the host to reuse that session instead of --login. It supports Chrome, Chromium, Brave, Edge, Arc, Vivaldi, ***, Yandex, and Naver Whale, auto-picks the most recently used browser with a live LinkedIn session (pass a browser name to target one), writes the same ~/.linkedin-mcp/ profile Docker mounts, and the Docker bridge still narrows to the minimal auth cookie subset it uses for a normal session. Cookies under Chrome 127+ app-bound encryption cannot be imported; use --login in that case.

Step 2: Configure Claude Desktop with Docker

json
{
  "mcpServers": {
    "linkedin": {
      "command": "docker",
      "args": [
        "run", "--rm", "-i",
        "-v", "~/.linkedin-mcp:/home/pwuser/.linkedin-mcp",
        "stickerdaniel/linkedin-mcp-server:latest"
      ]
    }
  }
}

Note: Docker containers don't have a display server, so you can't use the --login command in Docker. Create a source profile on your host first.

Note: stdio is the default transport. Add --transport streamable-http only when you specifically want HTTP mode.

Note: Tool calls are serialized within one server process to protect the shared LinkedIn browser session. Concurrent client requests queue instead of running in parallel. Use LOG_LEVEL=DEBUG to see scraper lock logs.

Environment Variables

VariableDefaultDescription
USER_DATA_DIR~/.linkedin-mcp/profilePath to persistent browser profile directory
LOG_LEVELWARNINGLogging level: DEBUG, INFO, WARNING, ERROR
TIMEOUT5000Browser timeout in milliseconds
TOOL_TIMEOUT180Per-tool MCP execution timeout in seconds. Increase further for heavy scrapes (multi-section profiles, cold-start Chromium, slow networks/containers).
LOGIN_TIMEOUT1800Manual login wait timeout in seconds (0 = no limit). Applies to the host-side --login browser; the container itself never opens one.
LOGIN_INLINE_WAIT25Bounded inline wait (seconds, max 45) for a tool call to resume after login completes. No effect in containers: the Docker runtime never opens a login window and raises a host-login-required error instead, so the session must be created on the host with --login.
AUTO_IMPORT_FROM_BROWSERon by defaultAuto-import a LinkedIn session from a locally logged-in browser on the first no-session tool call, before falling back to manual login. On by default across interactive and non-interactive desktop runs; set false to require --login / --import-from-browser. No effect in containers (no host browser or keychain) or on a non-loopback HTTP bind. On macOS the OS keychain may prompt once for Safe Storage access.
USER_AGENT-Custom browser user agent
TRANSPORTstdioTransport mode: stdio, streamable-http
HOST127.0.0.1HTTP server host (for streamable-http transport)
PORT8000HTTP server port (for streamable-http transport)
HTTP_PATH/mcpHTTP server path (for streamable-http transport)
SLOW_MO0Delay between browser actions in ms (debugging)
VIEWPORT1280x720Browser viewport size as WIDTHxHEIGHT
CHROME_PATH-Path to Chrome/Chromium executable (rarely needed in Docker)
LINKEDIN_EXPERIMENTAL_PERSIST_DERIVED_SESSIONfalseExperimental: reuse checkpointed derived Linux runtime profiles across Docker restarts instead of fresh-bridging each startup
LINKEDIN_TRACE_MODEon_errorTrace/log retention mode: on_error keeps ephemeral artifacts only when a failure occurs, always keeps every run, off disables trace persistence

Example with custom timeouts:

json
{
  "mcpServers": {
    "linkedin": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-v", "~/.linkedin-mcp:/home/pwuser/.linkedin-mcp",
        "-e", "TIMEOUT=10000",
        "-e", "TOOL_TIMEOUT=300",
        "stickerdaniel/linkedin-mcp-server"
      ]
    }
  }
}

Repository

  • Source: https://github.com/stickerdaniel/linkedin-mcp-server
  • License: Apache 2.0

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