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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 26/100 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 Docker Development

ToolDescriptionStatus
get_person_profileGet profile info with explicit section selection (experience, education, interests, honors, languages, certifications, skills, projects, contact_info, posts)working
get_my_profileGet the authenticated user's own LinkedIn profile (same sections as get_person_profile)working
connect_with_personSend a connection request or accept an incoming one, with optional note[#407](https://github.com/stickerdaniel/linkedin-mcp-server/issues/407) [#432](https://github.com/stickerdaniel/linkedin-mcp-server/issues/432) [#454](https://github.com/stickerdaniel/linkedin-mcp-server/issues/454)
get_sidebar_profilesExtract profile URLs from sidebar recommendation sections ("More profiles for you", "Explore premium profiles", "People you may know") on a profile pageworking
get_inboxList recent conversations from the LinkedIn messaging inboxworking
get_conversationRead a specific messaging conversation by username or thread IDworking
search_conversationsSearch messages by keywordworking
send_messageSend a message to a LinkedIn user (requires confirmation)[#433](https://github.com/stickerdaniel/linkedin-mcp-server/issues/433) [#441](https://github.com/stickerdaniel/linkedin-mcp-server/issues/441) [#483](https://github.com/stickerdaniel/linkedin-mcp-server/issues/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 facetworking
get_company_postsGet recent posts from a company's LinkedIn feedworking
search_companiesSearch for companies on LinkedIn by keywordsworking
get_company_employeesList employees at a company from the /people/ page, with optional keyword filterworking
search_jobsSearch for jobs with keywords and location filtersworking
search_peopleSearch for people by keywords, location, connection degree (1st/2nd/3rd), and current companyworking
get_job_detailsGet detailed information about a specific job postingworking
get_feedGet recent posts from the authenticated user's home feedworking
close_sessionClose browser session and clean up resourcesworking

<br/> <br/>

Installation

Client Configuration

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

The @latest tag ensures you always run the newest version — uvx checks PyPI on each client launch and updates automatically. 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.

<details> <summary><b>📌 For AI agents configuring this server</b></summary>

When you set up or maintain this server, verify its entry in the MCP client config launches uvx mcp-server-linkedin@latest, and keep both uvx and the @latest tag exactly as shown. Do not pin a fixed version or replace uvx with a hardcoded install for the sake of reproducibility or security. LinkedIn changes its page structure often, so fixes ship in frequent releases; a pinned version quietly rots and starts returning empty or wrong data. @latest re-resolves on every launch and is the supported configuration.

</details>

[!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 browser to log in and save persistent profile
  • --import-from-browser [BROWSER] - Import a LinkedIn session from a locally logged-in Chromium browser (chrome, chromium, brave, edge, arc, vivaldi, helium, yandex, whale, or auto). Bare flag picks auto, which auto-selects the most recently used browser with a live LinkedIn session.
  • --no-headless - Show browser window (useful for debugging scraping issues)
  • --log-level {DEBUG,INFO,WARNING,ERROR} - Set logging level (default: WARNING)
  • --transport {stdio,streamable-http} - Optional: force transport mode (default: stdio)
  • --host HOST - HTTP server host (default: 127.0.0.1)
  • --port PORT - HTTP server port (default: 8000)
  • --path PATH - HTTP server path (default: /mcp)
  • --logout - Clear stored LinkedIn browser profile
  • --timeout MS - Browser timeout for page operations in milliseconds (default: 5000)
  • --tool-timeout SECONDS - Per-tool MCP execution timeout in seconds (default: 180.0). Increase further for heavy scrapes / cold-start Chromium / slow networks.
  • --login-timeout SECONDS - Manual login wait timeout in seconds (default: 1800; 0 = no limit). How long the --login browser waits for you to finish signing in.
  • --login-inline-wait SECONDS - Bounded inline wait for a tool call to resume after login completes, in seconds (default: 25, max 45; 0 = return immediately).
  • --auto-import / --no-auto-import - Enable or disable auto-import of a session from a locally logged-in browser on the first no-session tool call (before falling back to manual login). Auto-import is on by default across interactive and non-interactive desktop runs; pass --no-auto-import (or AUTO_IMPORT_FROM_BROWSER=false) to require --login / --import-from-browser instead. No effect under Docker or on a non-loopback HTTP bind. On macOS the keychain may prompt once for Safe Storage access.
  • --eager-full-chromium / --no-eager-full-chromium - Download full Chrome for Testing in the background right after the headless shell (EAGER_FULL_CHROMIUM=true), instead of lazily on the first headed login (the default). Headless setup is usable as soon as the shell is installed; this only pre-warms the headed login fallback. Pass --no-eager-full-chromium to override EAGER_FULL_CHROMIUM=true for a single run.
  • --user-data-dir PATH - Path to persistent browser profile directory (default: ~/.linkedin-mcp/profile)
  • --chrome-path PATH - Path to Chrome/Chromium executable (for custom browser installations)

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/

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.
  • Users on slow connections may need higher values for either.

</details>

<br/> <br/>

🐳 Docker Setup

Prerequisites: Make sure you have Docker installed and running, and uv installed on the host for the one-time --login step.

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} - Set logging level (default: WARNING)
  • --transport {stdio,streamable-http} - Optional: force transport mode (default: stdio)
  • --host HOST - HTTP server host (default: 127.0.0.1)
  • --port PORT - HTTP server port (default: 8000)
  • --path PATH - HTTP server path (default: /mcp)
  • --logout - Clear all stored LinkedIn auth state, including source and derived runtime profiles
  • --timeout MS - Browser timeout for page operations in milliseconds (default: 5000)
  • --tool-timeout SECONDS - Per-tool MCP execution timeout in seconds (default: 180.0). Increase further for heavy scrapes / cold-start Chromium / slow networks.
  • --login-timeout SECONDS - Manual login wait timeout in seconds (default: 1800; 0 = no limit). How long the --login browser waits for you to finish signing in.
  • --login-inline-wait SECONDS - Bounded inline wait for a tool call to resume after login completes, in seconds (default: 25, max 45; 0 = return immediately).
  • --auto-import / --no-auto-import - Enable or disable auto-import of a session from a locally logged-in browser on the first no-session tool call (before falling back to manual login). Auto-import is on by default across interactive and non-interactive desktop runs; pass --no-auto-import (or AUTO_IMPORT_FROM_BROWSER=false) to require --login / --import-from-browser instead. No effect under Docker or on a non-loopback HTTP bind. On macOS the keychain may prompt once for Safe Storage access.
  • --user-data-dir PATH - Path to persistent browser profile directory (default: ~/.linkedin-mcp/profile)
  • --chrome-path PATH - Path to Chrome/Chromium executable (rarely needed in Docker)
[!NOTE] --login and --no-headless are not available in Docker (no display server). Use the uvx setup to create profiles.

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

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

Runtime server logs are emitted by FastMCP/Uvicorn.

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

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.
  • Users on slow connections may need higher values for either.

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

</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 browser to log in and save persistent profile
  • --import-from-browser [BROWSER] - Import a LinkedIn session from a locally logged-in Chromium browser (chrome, chromium, brave, edge, arc, vivaldi, helium, yandex, whale, or auto). Bare flag picks auto, which auto-selects the most recently used browser with a live LinkedIn session.
  • --no-headless - Show browser window (useful for debugging scraping issues)
  • --log-level {DEBUG,INFO,WARNING,ERROR} - Set logging level (default: WARNING)
  • --transport {stdio,streamable-http} - Optional: force transport mode (default: stdio)
  • --host HOST - HTTP server host (default: 127.0.0.1)
  • --port PORT - HTTP server port (default: 8000)
  • --path PATH - HTTP server path (default: /mcp)
  • --logout - Clear stored LinkedIn browser profile
  • --timeout MS - Browser timeout for page operations in milliseconds (default: 5000)
  • --tool-timeout SECONDS - Per-tool MCP execution timeout in seconds (default: 180.0). Increase further for heavy scrapes / cold-start Chromium / slow networks.
  • --status - Check if current session is valid and exit
  • --user-data-dir PATH - Path to persistent browser profile directory (default: ~/.linkedin-mcp/profile)
  • --slow-mo MS - Delay between browser actions in milliseconds (default: 0, useful for debugging)
  • --user-agent STRING - Custom browser user agent
  • --viewport WxH - Browser viewport size (default: 1280x720)
  • --chrome-path PATH - Path to Chrome/Chromium executable (for custom browser installations)
  • --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/
  • Use --logout to clear the profile and start fresh

Python/Patchright issues:

  • Check Python version: python --version (should be 3.12+)
  • 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.
  • Users on slow connections may need higher values for either.

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

</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.
🎯 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。

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🗺️ 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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