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linkedin-mcp-server MCP工具
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linkedin-mcp-server MCP工具

基于 Python · 让 AI 助手直接操作你的系统与工具
英文名:linkedin-mcp-server
⭐ 1.9k Stars 🍴 347 Forks 💻 Python 📄 Apache-2.0 🏷 AI 8.2分
8.2AI 综合评分
MCP服务LinkedIn集成AI代理Claude插件Python开发
✦ AI Skill Hub 推荐

经 AI Skill Hub 精选评估,linkedin-mcp-server MCP工具 获评「强烈推荐」。已获得 1.9k 颗 GitHub Star,这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 8.2 分,适合有一定技术背景的用户使用。

📚 深度解析

linkedin-mcp-server MCP工具 是一款基于 MCP(Model Context Protocol)标准协议的 AI 工具扩展。MCP 协议由 Anthropic 开发并开源,旨在建立 AI 模型与外部工具之间的标准化通信接口,目前已被 Claude Desktop、Claude Code、Cursor 等主流 AI 工具采纳。

通过安装 linkedin-mcp-server MCP工具,你的 AI 助手将获得额外的工具调用能力,可以用自然语言直接操控该工具的功能,无需学习复杂的命令行语法。MCP 工具的核心价值在于"一次配置,永久增强"——配置完成后,每次与 AI 对话时都可以无缝调用这些工具。

在技术实现上,MCP 工具通过标准的 JSON-RPC 协议与 AI 客户端通信,工具的功能以"工具列表"的形式暴露给 AI 模型,AI 可以按需调用。linkedin-mcp-server MCP工具 提供了结构化的工具调用接口,使 AI 模型能够精确地理解和使用每个功能点,显著降低 AI 在工具使用上的错误率。

与传统的 API 集成相比,MCP 工具的优势在于无需编写代码——用户只需在配置文件中添加几行 JSON,即可让 AI 获得全新能力。AI Skill Hub 将 linkedin-mcp-server MCP工具 评为 AI 评分 8.2 分,属于同类工具中的优质选择。

📋 工具概览

linkedin-mcp-server MCP工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

GitHub Stars
⭐ 1.9k
开发语言
Python
支持平台
Windows / macOS / Linux
维护状态
正常维护,社区驱动
开源协议
Apache-2.0
AI 综合评分
8.2 分
工具类型
MCP工具
Forks
347

📖 中文文档

以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

linkedin-mcp-server MCP工具 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。

📌 核心特色
  • 通过标准 MCP 协议与 Claude、Cursor 等主流 AI 客户端深度集成
  • 提供结构化工具调用接口,显著降低 AI 集成复杂度
  • 支持 Claude Desktop 和 Claude Code 无缝接入,开箱即用
  • 可与其他 MCP 工具组合叠加,构建完整 AI 工作站
  • 轻量无侵入设计,不影响现有系统架构
🎯 主要使用场景
  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/stickerdaniel/linkedin-mcp-server

# 方式二:手动配置 claude_desktop_config.json
{
  "mcpServers": {
    "linkedin-mcp-server-mcp--": {
      "command": "npx",
      "args": ["-y", "linkedin-mcp-server"]
    }
  }
}

# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
📋 安装步骤说明
  1. 确认已安装 Node.js(v18 或以上版本)
  2. 打开 Claude Desktop 或 Claude Code 的 MCP 配置文件
  3. 按「交给 Agent 安装 → Claude Desktop」标签中的 JSON 配置填入 mcpServers 字段
  4. 保存配置文件并重启 Claude 客户端
  5. 重启后,在对话中即可使用本工具
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 安装后在 Claude 对话中直接使用
# 示例:
用户: 请帮我用 linkedin-mcp-server MCP工具 执行以下任务...
Claude: [自动调用 linkedin-mcp-server MCP工具 MCP 工具处理请求]

# 查看可用工具列表
# 在 Claude 中输入:"列出所有可用的 MCP 工具"
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
// claude_desktop_config.json 配置示例
{
  "mcpServers": {
    "linkedin-mcp-server_mcp__": {
      "command": "npx",
      "args": ["-y", "linkedin-mcp-server"],
      "env": {
        // "API_KEY": "your-api-key-here"
      }
    }
  }
}

// 保存后重启 Claude Desktop 生效
📑 README 深度解析 真实文档 完整度 34/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

MCP Server for LinkedIn

<p align="left"> <a href="https://pypi.org/project/mcp-server-linkedin/" target="_blank"><img src="https://img.shields.io/pypi/v/mcp-server-linkedin?color=blue" alt="PyPI"></a> <a href="https://github.com/stickerdaniel/linkedin-mcp-server/actions/workflows/ci.yml" target="_blank"><img src="https://github.com/stickerdaniel/linkedin-mcp-server/actions/workflows/ci.yml/badge.svg?branch=main" alt="CI Status"></a> <a href="https://github.com/stickerdaniel/linkedin-mcp-server/actions/workflows/release.yml" target="_blank"><img src="https://github.com/stickerdaniel/linkedin-mcp-server/actions/workflows/release.yml/badge.svg?branch=main" alt="Release"></a> <a href="https://github.com/stickerdaniel/linkedin-mcp-server/blob/main/LICENSE" target="_blank"><img src="https://img.shields.io/badge/License-Apache%202.0-%233fb950?labelColor=32383f" alt="License"></a> </p>

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.

An MCP server that lets AI assistants like Claude read LinkedIn data through your own logged-in browser session. Access profiles and companies, search for jobs, or get job details.

3. Install dependencies

uv sync uv sync --group dev

Installation Methods - MCP Server for LinkedIn

uvx Install MCP Bundle Codex Plugin Docker Development

ToolDescription
get_person_profileGet profile info with explicit section selection (experience, education, interests, honors, languages, certifications, skills, projects, contact_info, posts)
get_my_profileGet the authenticated user's own LinkedIn profile (same sections as get_person_profile)
connect_with_personSend a connection request or accept an incoming one, with optional note
get_sidebar_profilesExtract profile URLs from sidebar recommendation sections ("More profiles for you", "Explore premium profiles", "People you may know") on a profile page
get_inboxList recent conversations from the LinkedIn messaging inbox
get_conversationRead a specific messaging conversation by username or thread ID
search_conversationsSearch messages by keyword
send_messageCompose/send a new message to a LinkedIn user (requires confirmation; profile-based targeting may open a separate DM instead of replying in an existing thread — see #483)
get_company_profileExtract company information with explicit section selection (posts, jobs); about-section references may include a company_urn entry carrying the numeric id used by LinkedIn's people-search currentCompany URL facet
get_company_postsGet recent posts from a company's LinkedIn feed
search_companiesSearch for companies on LinkedIn by keywords
get_company_employeesList employees at a company from the /people/ page, with optional keyword filter
search_jobsSearch for jobs with keywords and location filters
get_saved_jobsList job postings saved by the authenticated user
search_peopleSearch for people by keywords, location, connection degree (1st/2nd/3rd), and current company
get_job_detailsGet detailed information about a specific job posting
get_feedGet recent posts from the authenticated user's home feed
search_postsSearch posts/content globally by keyword (the "Posts" tab) with an optional recency filter (past-24h/past-week/past-month)
close_sessionClose browser session and clean up resources

<br/> <br/>

Installation

Client Configuration

{
  "mcpServers": {
    "mcp-server-linkedin": {
      "command": "uvx",
      "args": ["mcp-server-linkedin@latest"],
      "env": { "UV_HTTP_TIMEOUT": "300" }
    }
  }
}

The @latest tag turns on automatic updates, which keep the server working with LinkedIn's current page structure. The server starts quickly, prepares the shared Patchright Chromium browser cache in the background under ~/.linkedin-mcp/patchright-browsers, and opens a LinkedIn login browser window on the first tool call that needs authentication.

AI agent? Get a quick confirmation from the user before enabling automatic updates.

[!NOTE] Early tool calls may return a setup/authentication-in-progress error until browser setup or login finishes. If you prefer to create a session explicitly, run uvx mcp-server-linkedin@latest --login.

uvx Setup Help

<details> <summary><b>🔧 Configuration</b></summary>

Transport Modes:

  • Default (stdio): Standard communication for local MCP servers
  • Streamable HTTP: For web-based MCP server
  • If no transport is specified, the server defaults to stdio
  • An interactive terminal without explicit transport shows a chooser prompt

CLI Options:

  • --login - Open a browser to sign in and save the session
  • --import-from-browser [BROWSER] - Reuse a session from a locally signed-in Chromium browser (chrome, chromium, brave, edge, arc, vivaldi, helium, yandex, whale, auto). Bare flag picks auto, the most recently used browser with a live LinkedIn session.
  • --logout - Clear the stored session
  • --no-headless - Show the browser window (useful for debugging)
  • --log-level {DEBUG,INFO,WARNING,ERROR} - Logging level (default: WARNING)
  • --transport {stdio,streamable-http} - Force the transport mode (default: stdio)
  • --host HOST / --port PORT / --path PATH - HTTP server address (defaults: 127.0.0.1, 8000, /mcp)
  • --timeout MS - Timeout for a single page operation (default: 5000)
  • --tool-timeout SECONDS - Timeout for a whole tool call (default: 180). Raise it for heavy scrapes, slow networks, or a cold-start browser.
  • --login-timeout SECONDS - How long the login browser waits for you to finish signing in (default: 1800; 0 = no limit). --login-viewer ends the session after 30 minutes either way.
  • --login-viewer - Docker only: show the --login browser at a token-protected URL on port 6080 (see Authentication)
  • --login-inline-wait SECONDS - How long a tool call waits for a login to finish before telling the model to retry (default: 25, max 45; 0 = return at once)
  • --browser-wait SECONDS - How long to wait for another server process to hand over the shared browser (default: 25, max 45; 0 = report busy at once). Only matters with several MCP clients running at once.
  • --browser-min-hold SECONDS - Shortest time this process keeps the shared browser before handing it over (default: 20). Clamped to 3 seconds below --browser-wait, so raise that one along with it. Higher means fewer browser restarts but longer waits for other clients.
  • --browser-idle-timeout SECONDS - Close an idle browser and release the profile after this long without a tool call (default: 600; 0 = keep it open)
  • --auto-import / --no-auto-import - Import a session from a signed-in local browser on the first tool call that needs one, before falling back to manual login (default: on). Skipped in Docker, behind a proxy, and on a non-loopback HTTP bind. On macOS the keychain may prompt once.
  • --user-data-dir PATH - Browser profile directory (default: ~/.linkedin-mcp/profile). Rotating or clearing a session deletes this directory and its parent, which holds the stored cookies and derived profiles.
  • --claim-profile-root - Take over a profile directory the server will not claim on its own, such as one whose parent already holds other files. Needed once per directory.
  • --chrome-path PATH - Path to a Chrome/Chromium executable
  • --proxy-server URL - Route browser traffic through a proxy, as scheme://host:port. Set the password via PROXY_PASSWORD, which keeps it out of the process list.

Import a session from your everyday browser:

If you are already signed into LinkedIn in Chrome, Chromium, Brave, Edge, Arc, Vivaldi, Helium, Yandex, or Naver Whale, you can skip the manual --login step and reuse that session:

```bash

MCP Bundle Setup Help

<details> <summary><b>❗ Troubleshooting</b></summary>

First-time setup behavior:

  • Claude Desktop starts the bundle immediately; browser setup continues in the background
  • If the Patchright Chromium browser is still downloading, retry the tool after a short wait
  • Managed browser downloads are shared under ~/.linkedin-mcp/patchright-browsers/
  • The browser cache keeps growing: Patchright keeps an old Chromium revision for as long as any installed version still references it, so an upgrade can leave both on disk. The server logs a warning naming what it holds. To reclaim the space, stop every LinkedIn MCP Server instance, delete ~/.linkedin-mcp/patchright-browsers/, and let the next launch download the current browser.
  • Windows, the bundle exits with DLL load failed while importing _greenlet: install the Microsoft Visual C++ Redistributable, or reinstall a bundle pinning greenlet 3.5.5 or newer, whose published Windows wheels carry the C++ runtime inside the extension again. A bundle pinning greenlet 3.3.1 through 3.5.4 needs MSVCP140.dll from that redistributable, which neither the python.org installer nor the uv-managed builds carry, and a greenlet built from source can need it at any version. The server names this itself on startup, and only after checking that the loader cannot produce that DLL. Reported as greenlet#525, fixed in greenlet#526.

Login issues:

  • Make sure you have only one active LinkedIn session at a time
  • LinkedIn may require a login confirmation in the LinkedIn mobile app for --login
  • LinkedIn may show a captcha challenge during login. Run uvx mcp-server-linkedin@latest --login which opens a browser where you can solve captchas manually. See the uvx setup for prerequisites.

Timeout issues:

  • Page operations failing (elements not found, navigation hangs): increase the browser page-op timeout — --timeout 10000 or TIMEOUT=10000 (milliseconds, default 5000).
  • Entire tool calls timing out (e.g. multi-section profiles, cold-start Chromium, slow containers): increase the per-tool execution timeout — --tool-timeout 300 or TOOL_TIMEOUT=300 (seconds, default 180).
  • First tool call with no session: if a locally logged-in browser has a live LinkedIn session, the server auto-imports it (see AUTO_IMPORT_FROM_BROWSER / --auto-import) instead of forcing a manual login. On macOS the keychain may prompt once for Safe Storage access. If no importable browser session exists, it falls back to opening a login window and waits up to LOGIN_INLINE_WAIT seconds (default 25, max 45; --login-inline-wait) so a quick sign-in resolves in one call. If the wait elapses, the tool returns a pending signal and the model retries in about 30 seconds. Neither the auto-import nor the inline wait applies under Docker or when the server is bound to a non-loopback HTTP host. Create the session on the host with --login, or use the explicit Docker --login --login-viewer command.
  • Users on slow connections may need higher values for either.

Told to run --login on the host when you already did:

  • If tool calls answer "No valid LinkedIn session is available in Docker" on a machine that is not a container, the runtime was misdetected. This happened on Linux hosts running a Docker daemon for unrelated services. Set LINKEDIN_MCP_CONTAINER=false to override the detection; true forces the opposite.

</details>

<br/> <br/>

🐳 Docker Setup

Prerequisites: Make sure Docker is installed and running.

Docker Setup Help

<details> <summary><b>🔧 Configuration</b></summary>

Transport Modes:

  • Default (stdio): Standard communication for local MCP servers
  • Streamable HTTP: For a web-based MCP server
  • If no transport is specified, the server defaults to stdio
  • An interactive terminal without explicit transport shows a chooser prompt

CLI Options:

  • --log-level {DEBUG,INFO,WARNING,ERROR} - Logging level (default: WARNING)
  • --transport {stdio,streamable-http} - Force the transport mode (default: stdio)
  • --host HOST / --port PORT / --path PATH - HTTP server address (defaults: 127.0.0.1, 8000, /mcp)
  • --logout - Clear the stored session and every profile derived from it
  • --timeout MS - Timeout for a single page operation (default: 5000)
  • --tool-timeout SECONDS - Timeout for a whole tool call (default: 180). Raise it for heavy scrapes, slow networks, or a cold-start browser.
  • --login-timeout SECONDS - How long the login browser waits for you to finish signing in (default: 1800; 0 = no limit). --login-viewer ends the session after 30 minutes either way.
  • --login-viewer - With --login, show the login browser at a token-protected URL on port 6080. Needs the profile mount from Authentication.
  • --login-inline-wait SECONDS - How long a tool call waits for a login to finish before telling the model to retry (default: 25, max 45; 0 = return at once)
  • --browser-wait SECONDS - How long to wait for another server process to hand over the shared browser (default: 25, max 45; 0 = report busy at once). Only matters with several MCP clients running at once.
  • --browser-min-hold SECONDS - Shortest time this process keeps the shared browser before handing it over (default: 20). Clamped to 3 seconds below --browser-wait, so raise that one along with it. Higher means fewer browser restarts but longer waits for other clients.
  • --browser-idle-timeout SECONDS - Close an idle browser and release the profile after this long without a tool call (default: 600; 0 = keep it open)
  • --auto-import / --no-auto-import - Import a session from a signed-in local browser on the first tool call that needs one, before falling back to manual login (ignored in Docker). On macOS the keychain may prompt once.
  • --user-data-dir PATH - Browser profile directory (default: ~/.linkedin-mcp/profile). Rotating or clearing a session deletes this directory and its parent, which holds the stored cookies and derived profiles.
  • --claim-profile-root - Take over a profile directory the server will not claim on its own, such as one whose parent already holds other files. Needed once per directory.
  • --chrome-path PATH - Path to a Chrome/Chromium executable (rarely needed in Docker)
  • --proxy-server URL - Route browser traffic through a proxy, as scheme://host:port. Set the password via PROXY_PASSWORD, which keeps it out of the process list.
[!NOTE] Plain --login still has no visible window in Docker. Add --login-viewer and publish 127.0.0.1:6080:6080 only for the one-shot login command. Docker is already headed by default, so --no-headless changes nothing. The experimental --daemon is ignored in Docker because its owner can outlive the virtual display.

HTTP Mode Example (for web-based MCP clients):

Bash / macOS / Linux:

docker run -it --rm \
  -v ~/.linkedin-mcp:/home/pwuser/.linkedin-mcp \
  -p 127.0.0.1:8080:8080 \
  stickerdaniel/linkedin-mcp-server:latest \
  --transport streamable-http --host 0.0.0.0 --port 8080 --path /mcp

PowerShell (Windows):

$sessionDir = Join-Path $env:USERPROFILE ".linkedin-mcp"
docker run -it --rm `
  -v "${sessionDir}:/home/pwuser/.linkedin-mcp" `
  -p 127.0.0.1:8080:8080 `
  stickerdaniel/linkedin-mcp-server:latest `
  --transport streamable-http --host 0.0.0.0 --port 8080 --path /mcp

Both halves of that are needed, and they do different jobs. --host 0.0.0.0 makes the server reachable inside the container: a process bound to 127.0.0.1 in there cannot be reached through a published port at all. The 127.0.0.1: in front of -p is what limits it outside, to this machine. Drop that prefix and Docker publishes on every interface, which puts an endpoint with no authentication on your network. The server cannot tell the two apart, so it warns either way.

Loopback publishing limits this to the machine, not to the container. Other containers on the same host can still reach it through host.docker.internal wherever that name resolves, which is the default on Docker Desktop and OrbStack but not on native Linux Docker.

Runtime server logs are emitted by FastMCP/Uvicorn.

The HTTP server answers requests addressed to localhost or to the address it is bound to, and refuses others with 421. That is what stops a website you merely visit from pointing a domain at this server and using your LinkedIn session through your own browser.

Reaching the server by any other name is refused, including a machine name on your network and the public name in front of a reverse proxy. Either have the proxy rewrite the upstream Host to the backend address, or name the host you serve it under:

FASTMCP_HTTP_ALLOWED_HOSTS='["mcp.example"]'

That permits exactly that name and keeps refusing everything else. The endpoint still has no authentication, so anything reachable beyond your own machine belongs behind something that provides it.

Test with mcp inspector:

  1. Install and run mcp inspector
     @modelcontextprotocol/inspector
  2. Click pre-filled token url to open the inspector in your browser
  3. Select Streamable HTTP as Transport Type
  4. Set URL to http://localhost:8080/mcp
  5. Connect
  6. Test tools

</details>

<details> <summary><b>❗ Troubleshooting</b></summary>

Docker issues:

  • Make sure Docker is installed
  • Check if Docker is running: docker ps
  • Permission errors on ~/.linkedin-mcp: an older rootful Docker run may have created the directory as root. Fix it with sudo chown -R "$(id -u):$(id -g)" ~/.linkedin-mcp.

Login issues:

  • Make sure you have only one active LinkedIn session at a time
  • LinkedIn may require a login confirmation in the LinkedIn mobile app for --login
  • LinkedIn may show a captcha challenge during login. Run uvx mcp-server-linkedin@latest --login which opens a browser where you can solve captchas manually. See the uvx setup for prerequisites.
  • If Docker auth becomes stale after you re-login on the host, restart Docker once so it can fresh-bridge from the new source session generation.

Timeout issues:

  • Page operations failing (elements not found, navigation hangs): increase the browser page-op timeout — --timeout 10000 or TIMEOUT=10000 (milliseconds, default 5000).
  • Entire tool calls timing out (e.g. multi-section profiles, cold-start Chromium, slow containers): increase the per-tool execution timeout — --tool-timeout 300 or TOOL_TIMEOUT=300 (seconds, default 180).
  • First tool call with no session: if a locally logged-in browser has a live LinkedIn session, the server auto-imports it (see AUTO_IMPORT_FROM_BROWSER / --auto-import) instead of forcing a manual login. On macOS the keychain may prompt once for Safe Storage access. If no importable browser session exists, it falls back to opening a login window and waits up to LOGIN_INLINE_WAIT seconds (default 25, max 45; --login-inline-wait) so a quick sign-in resolves in one call. If the wait elapses, the tool returns a pending signal and the model retries in about 30 seconds. Neither the auto-import nor the inline wait applies under Docker or when the server is bound to a non-loopback HTTP host. Create the session on the host with --login, or use the explicit Docker --login --login-viewer command.
  • Users on slow connections may need higher values for either.

Told to run --login on the host when you already did:

  • If tool calls answer "No valid LinkedIn session is available in Docker" on a machine that is not a container, the runtime was misdetected. This happened on Linux hosts running a Docker daemon for unrelated services. Set LINKEDIN_MCP_CONTAINER=false to override the detection; true forces the opposite.

Using a proxy:

Most people should not use one. LinkedIn's own guidance for reducing security challenges is to avoid a VPN or proxy, and it scores the addresses a session signs in from. A home connection you have used for years is a trust signal; a commercial exit node with a history you cannot see is not, and switching to one is itself the kind of change that triggers a checkpoint. A proxy is worth it in one case: the server runs somewhere its address is obviously a data centre, or in a different country from the account's history. Even then, a WireGuard or Tailscale exit node on your own home network beats any paid provider, because the address really is yours. If you do buy one, take a dedicated static ISP address and keep it, rather than a rotating residential pool.
  • Route the browser through a proxy with --proxy-server http://host:port (http, https, socks4 and socks5 are accepted). Only browser traffic is routed, not the MCP transport.
  • Credentials go in PROXY_USERNAME and PROXY_PASSWORD. There is no --proxy-password flag on purpose: command-line arguments are readable by every other user on the machine. PROXY_SERVER also accepts the combined http://user:pass@host:port form most providers hand out.
  • Chromium cannot authenticate to a SOCKS proxy, so credentials require an http(s) endpoint. If your provider only offers authenticated SOCKS5, run a local relay that holds the credentials and point the server at that.
  • Local addresses go through the proxy too. Chromium's usual direct route for localhost is removed when a proxy is set, so add PROXY_BYPASS=localhost,127.0.0.1,::1 if you need local targets reached directly.
  • Auto-import is skipped while a proxy is configured: a session taken from a local browser was created on your real address, and moving it to the proxy is the very change that triggers a checkpoint. Use --login.
  • A wrong proxy password does not report itself: Chromium retries the authentication challenge until the page times out, so it surfaces as a timeout or a failed sign-in. If sessions stop working right after you add a proxy, check the credentials before assuming the session expired.
  • Set the proxy up before creating the session. Run --login with the proxy already configured. Turning a proxy on for an existing profile moves a logged-in session to a new IP, which is what triggers a LinkedIn checkpoint. The same applies to --import-from-browser, which imports a session created on your real IP. Use a sticky session, not a rotating pool, for the same reason.

Custom Chrome path:

  • If Chrome is installed in a non-standard location, use --chrome-path /path/to/chrome
  • Can also set via environment variable: CHROME_PATH=/path/to/chrome
  • On macOS and Linux the browser must be at least as new as the one that last opened your profile, and the server refuses the launch otherwise. (Not on Windows: a browser there cannot be asked its version without starting one, so the check is off.) An older browser can silently drop stores a newer one wrote, the saved session among them, and the failure then looks exactly like an expired login. The message names both versions. Going back to the bundled Chromium after running a newer Chrome once is the usual way to meet this; either run the newer browser again, whichever one that was, or run --login, which moves the stored session aside and signs in fresh with the browser you have. --logout also clears it but discards the old session instead of keeping it recoverable, and it asks for confirmation on the terminal, so it is not usable from a server an MCP client started.
  • Only Chrome, Chromium and Chrome for Testing are compared this way. Forks number themselves differently (Vivaldi is on 7.x, Edge's build number sits far below Chrome's under the same major), so pointing CHROME_PATH at one turns the check off rather than producing a refusal nothing could satisfy.
  • In the documented Docker setup this check does not apply. The container never opens the profile you created with --login; it derives its own from your cookies, and by default rebuilds that from scratch on every start, so there is nothing for an older image to downgrade. With EXPERIMENTAL_PERSIST_DERIVED_RUNTIME the derived profile is kept, and an image tag that moves backwards then throws it away and re-derives it, again with nothing for you to do. The check matters on the host, where the server opens that profile directly. Not during --login itself, which moves the old profile aside before it starts a browser and so can never trip it.

</details>

<br/> <br/>

🐍 Local Setup (Develop & Contribute)

Contributions are welcome! See CONTRIBUTING.md for architecture guidelines and checklists. Please open an issue first to discuss the feature or bug fix before submitting a PR.

Prerequisites: Git and uv installed

Installation

```bash

2. Install UV package manager (if not already installed)

curl -LsSf https://astral.sh/uv/install.sh | sh

4. Install pre-commit hooks

uv run pre-commit install

Local Setup Help

<details> <summary><b>🔧 Configuration</b></summary>

CLI Options:

  • --login - Open a browser to sign in and save the session
  • --import-from-browser [BROWSER] - Reuse a session from a locally signed-in Chromium browser (chrome, chromium, brave, edge, arc, vivaldi, helium, yandex, whale, auto). Bare flag picks auto, the most recently used browser with a live LinkedIn session.
  • --status - Check whether the stored session is valid, then exit
  • --logout - Clear the stored session
  • --no-headless - Show the browser window (useful for debugging)
  • --log-level {DEBUG,INFO,WARNING,ERROR} - Logging level (default: WARNING)
  • --transport {stdio,streamable-http} - Force the transport mode (default: stdio)
  • --host HOST / --port PORT / --path PATH - HTTP server address (defaults: 127.0.0.1, 8000, /mcp)
  • --timeout MS - Timeout for a single page operation (default: 5000)
  • --tool-timeout SECONDS - Timeout for a whole tool call (default: 180). Raise it for heavy scrapes, slow networks, or a cold-start browser.
  • --user-data-dir PATH - Browser profile directory (default: ~/.linkedin-mcp/profile). Rotating or clearing a session deletes this directory and its parent, which holds the stored cookies and derived profiles.
  • --installer-temp-dir PATH - Parent directory for temporary files created during browser installation bootstrap (default: system temporary directory). Useful when system %TEMP% ancestry has non-standard ACLs or permissions.
  • --claim-profile-root - Take over a profile directory the server will not claim on its own, such as one whose parent already holds other files. Needed once per directory.
  • --slow-mo MS - Delay between browser actions (default: 0, useful for debugging)
  • --viewport WxH - Viewport size (default: 1280x720). Applies to windowless mode only; a headed launch uses the real window size.
  • --chrome-path PATH - Path to a Chrome/Chromium executable
  • --proxy-server URL - Route browser traffic through a proxy, as scheme://host:port. Set the password via PROXY_PASSWORD, which keeps it out of the process list.
  • --help - Show help
Note: Most CLI options have environment variable equivalents. See .env.example for details.

HTTP Mode Example (for web-based MCP clients):

uv run -m linkedin_mcp_server --transport streamable-http --host 127.0.0.1 --port 8000 --path /mcp

Claude Desktop:

{
  "mcpServers": {
    "mcp-server-linkedin": {
      "command": "uv",
      "args": ["--directory", "/path/to/linkedin-mcp-server", "run", "-m", "linkedin_mcp_server"]
    }
  }
}

stdio is used by default for this config.

</details>

<details> <summary><b>❗ Troubleshooting</b></summary>

Login issues:

  • Make sure you have only one active LinkedIn session at a time
  • LinkedIn may require a login confirmation in the LinkedIn mobile app for --login
  • LinkedIn may show a captcha challenge during login. The --login command opens a browser where you can solve it manually.

Scraping issues:

  • Use --no-headless to see browser actions and debug scraping problems
  • Add --log-level DEBUG to see more detailed logging

Session issues:

  • Browser profile is stored at ~/.linkedin-mcp/profile/
  • Managed browser downloads are cached at ~/.linkedin-mcp/patchright-browsers/, shared with the uvx and MCP Bundle installations
  • The browser cache keeps growing: Patchright keeps an old Chromium revision for as long as any installed version still references it, and a uv archive or a second worktree is such a reference. The server logs a warning naming what it holds. To reclaim the space, stop every LinkedIn MCP Server instance, delete ~/.linkedin-mcp/patchright-browsers/, and let the next launch download the current browser.
  • Use --logout to clear the profile and start fresh

Python/Patchright issues:

  • Check Python version: python --version (should be 3.12.4+)
  • Reinstall Patchright: uv run patchright install chromium
  • Reinstall dependencies: uv sync --reinstall

Timeout issues:

  • Page operations failing (elements not found, navigation hangs): increase the browser page-op timeout — --timeout 10000 or TIMEOUT=10000 (milliseconds, default 5000).
  • Entire tool calls timing out (e.g. multi-section profiles, cold-start Chromium, slow containers): increase the per-tool execution timeout — --tool-timeout 300 or TOOL_TIMEOUT=300 (seconds, default 180).
  • First tool call with no session: if a locally logged-in browser has a live LinkedIn session, the server auto-imports it (see AUTO_IMPORT_FROM_BROWSER / --auto-import) instead of forcing a manual login. On macOS the keychain may prompt once for Safe Storage access. If no importable browser session exists, it falls back to opening a login window and waits up to LOGIN_INLINE_WAIT seconds (default 25, max 45; --login-inline-wait) so a quick sign-in resolves in one call. If the wait elapses, the tool returns a pending signal and the model retries in about 30 seconds. Neither the auto-import nor the inline wait applies under Docker or when the server is bound to a non-loopback HTTP host. Create the session on the host with --login, or use the explicit Docker --login --login-viewer command.
  • Users on slow connections may need higher values for either.

Told to run --login on the host when you already did:

  • If tool calls answer "No valid LinkedIn session is available in Docker" on a machine that is not a container, the runtime was misdetected. This happened on Linux hosts running a Docker daemon for unrelated services. Set LINKEDIN_MCP_CONTAINER=false to override the detection; true forces the opposite.

Using a proxy:

Most people should not use one. LinkedIn's own guidance for reducing security challenges is to avoid a VPN or proxy, and it scores the addresses a session signs in from. A home connection you have used for years is a trust signal; a commercial exit node with a history you cannot see is not, and switching to one is itself the kind of change that triggers a checkpoint. A proxy is worth it in one case: the server runs somewhere its address is obviously a data centre, or in a different country from the account's history. Even then, a WireGuard or Tailscale exit node on your own home network beats any paid provider, because the address really is yours. If you do buy one, take a dedicated static ISP address and keep it, rather than a rotating residential pool.
  • Route the browser through a proxy with --proxy-server http://host:port (http, https, socks4 and socks5 are accepted). Only browser traffic is routed, not the MCP transport.
  • Credentials go in PROXY_USERNAME and PROXY_PASSWORD. There is no --proxy-password flag on purpose: command-line arguments are readable by every other user on the machine. PROXY_SERVER also accepts the combined http://user:pass@host:port form most providers hand out.
  • Chromium cannot authenticate to a SOCKS proxy, so credentials require an http(s) endpoint. If your provider only offers authenticated SOCKS5, run a local relay that holds the credentials and point the server at that.
  • Local addresses go through the proxy too. Chromium's usual direct route for localhost is removed when a proxy is set, so add PROXY_BYPASS=localhost,127.0.0.1,::1 if you need local targets reached directly.
  • Auto-import is skipped while a proxy is configured: a session taken from a local browser was created on your real address, and moving it to the proxy is the very change that triggers a checkpoint. Use --login.
  • A wrong proxy password does not report itself: Chromium retries the authentication challenge until the page times out, so it surfaces as a timeout or a failed sign-in. If sessions stop working right after you add a proxy, check the credentials before assuming the session expired.
  • Set the proxy up before creating the session. Run --login with the proxy already configured. Turning a proxy on for an existing profile moves a logged-in session to a new IP, which is what triggers a LinkedIn checkpoint. The same applies to --import-from-browser, which imports a session created on your real IP. Use a sticky session, not a rotating pool, for the same reason.

Custom Chrome path:

  • If Chrome is installed in a non-standard location, use --chrome-path /path/to/chrome
  • Can also set via environment variable: CHROME_PATH=/path/to/chrome
  • On macOS and Linux the browser must be at least as new as the one that last opened your profile, and the server refuses the launch otherwise. (Not on Windows: a browser there cannot be asked its version without starting one, so the check is off.) An older browser can silently drop stores a newer one wrote, the saved session among them, and the failure then looks exactly like an expired login. The message names both versions. Going back to the bundled Chromium after running a newer Chrome once is the usual way to meet this; either run the newer browser again, whichever one that was, or run --login, which moves the stored session aside and signs in fresh with the browser you have. --logout also clears it but discards the old session instead of keeping it recoverable, and it asks for confirmation on the terminal, so it is not usable from a server an MCP client started.
  • Only Chrome, Chromium and Chrome for Testing are compared this way. Forks number themselves differently (Vivaldi is on 7.x, Edge's build number sits far below Chrome's under the same major), so pointing CHROME_PATH at one turns the check off rather than producing a refusal nothing could satisfy.

</details>

<br/> <br/>

[!IMPORTANT] FAQ Is this safe to use? Will I get banned? This tool controls a real browser session; it doesn't exploit undocumented APIs or bypass authentication. LinkedIn's User Agreement prohibits automated access, and accounts using automated tools can be restricted or banned. Use at your own risk; there is no guarantee of account safety. If you encounter any issues, let me know in the Discussions. What if my agents execute too many actions? Tool calls run sequentially through a queue. You are responsible for the volume of automation you run; use it sparingly and prompt your agents responsibly.

🧩 Codex plugin

This repository includes an opt-in Codex plugin that bundles the MCP server and its LinkedIn workflow guidance. Add the repository marketplace, then install the plugin:

codex plugin marketplace add stickerdaniel/linkedin-mcp-server
codex plugin add linkedin-mcp-server@linkedin-mcp-server

The plugin pins the MCP package to the same version as the plugin release. It does not install by default or override the user's enabled state. The plugin can be disabled in Codex settings, and its bundled MCP server can be disabled independently in ~/.codex/config.toml:

[plugins."linkedin-mcp-server".mcp_servers.linkedin]
enabled = false

Installing or enabling the plugin does not open a browser or sign in. A LinkedIn data request may start the managed browser, import an existing local session, or require a visible login window.

<br/> <br/>

🎯 aiskill88 AI 点评 A 级 2026-05-21

高质量MCP集成方案,架构清晰维护活跃,1.9k星证明社区认可度高,对AI代理生态贡献显著。

📚 实用指南(长尾问题)
适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 构建多智能体协作系统的 Agent 开发者
最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • 生产部署优先使用 Docker Compose 隔离依赖,并挂载 volume 持久化数据
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • 容器内无法访问宿主机 localhost — 使用 host.docker.internal
  • Python 依赖冲突:建议用 venv / uv 隔离环境
部署方案
  • Docker:linkedin-mcp-server 提供官方镜像,docker compose up 一键启动
  • CLI:直接 npm install -g / pip install,命令行调用
  • 云端托管:可放在 Vercel / Railway / Fly.io 等 PaaS 平台
相关搜索
linkedin-mcp-server 中文教程linkedin-mcp-server 安装报错怎么办linkedin-mcp-server MCP 配置linkedin-mcp-server Docker 部署linkedin-mcp-server Agent 工作流linkedin-mcp-server 与同类工具对比linkedin-mcp-server 最佳实践linkedin-mcp-server 适合谁用

⚡ 核心功能

👥 适合谁
  • 需要让 Claude / Cursor 操作本地工具的 AI 工程师
  • 构建多智能体协作系统的 Agent 开发者
⭐ 最佳实践
  • 配置 MCP 服务器时建议使用 stdio 传输 + JSON-RPC,避免暴露公网
  • 生产部署优先使用 Docker Compose 隔离依赖,并挂载 volume 持久化数据
  • Agent 任务先做 dry-run 验证工具调用链,再开启自主执行
⚠️ 常见错误
  • API key 直接提交到 git 仓库(请用 .env 并加入 .gitignore)
  • MCP 配置路径拼错或权限不足,重启 Claude Desktop 才生效
  • 容器内无法访问宿主机 localhost — 使用 host.docker.internal
  • Python 依赖冲突:建议用 venv / uv 隔离环境

👥 适合人群

Claude Desktop / Claude Code 用户AI 工具开发者需要扩展 AI 能力的专业人士自动化工程师

🎯 使用场景

  • 在 Claude Desktop 对话中直接调用本地工具,实现 AI 与系统的深度联动
  • 通过自然语言驱动复杂的多步骤自动化任务,代替繁琐手动操作
  • 将多个 MCP 工具组合使用,构建个人专属 AI 工作站

⚖️ 优点与不足

✅ 优点
  • +Apache-2.0 协议,可免费商用
  • +标准化 MCP 协议,生态互联性强
  • +与 Claude 官方生态无缝对接
  • +即插即用,配置简单快捷
⚠️ 不足
  • 依赖 Claude 客户端,非 Claude 用户无法使用
  • MCP 协议仍在持续演进,接口可能变更
  • 需要一定的配置步骤
⚠️ 使用须知

AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。

建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。

📄 License 说明

✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。

🔗 相关工具推荐

📚 相关教程推荐
📰 相关 AI 新闻
🍿 AI 圈相关吃瓜
🗺️ 相关解决方案
🧩 你可能还需要
基于当前 Skill 的能力图谱,自动补全的工具组合

❓ 常见问题 FAQ

需要有效的LinkedIn账户凭证进行身份验证才能访问数据。
💡 AI Skill Hub 点评

AI Skill Hub 点评:linkedin-mcp-server MCP工具 的核心功能完整,质量优秀。对于Claude Desktop / Claude Code 用户来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。

⬇️ 获取与下载
⬇ 下载源码 ZIP

✅ Apache-2.0 协议 · 可免费商用 · 直接从 aiskill88 服务器下载,无需跳转 GitHub

📚 深入学习 linkedin-mcp-server MCP工具
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 linkedin-mcp-server
原始描述 开源MCP工具:Open-source MCP server for LinkedIn. Give Claude and any MCP-compatible AI assis。⭐1.9k · Python
Topics MCP服务LinkedIn集成AI代理Claude插件Python开发
GitHub https://github.com/stickerdaniel/linkedin-mcp-server
License Apache-2.0
语言 Python
🔗 原始来源
🐙 GitHub 仓库  https://github.com/stickerdaniel/linkedin-mcp-server

收录时间:2026-05-14 · 更新时间:2026-05-16 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。

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