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。
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。
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。
# 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"
// 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
<p align="left"> <a href="https://pypi.org/project/linkedin-scraper-mcp/" target="_blank"><img src="https://img.shields.io/pypi/v/linkedin-scraper-mcp?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>
Through this LinkedIn MCP server, AI assistants like Claude can connect to your LinkedIn. Access profiles and companies, search for jobs, or get job details.
uv sync uv sync --group dev
| Tool | Description | Status |
|---|---|---|
get_person_profile | Get profile info with explicit section selection (experience, education, interests, honors, languages, certifications, skills, projects, contact_info, posts) | working |
get_my_profile | Get the authenticated user's own LinkedIn profile (same sections as get_person_profile) | working |
connect_with_person | Send 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) [#448](https://github.com/stickerdaniel/linkedin-mcp-server/issues/448) |
get_sidebar_profiles | Extract profile URLs from sidebar recommendation sections ("More profiles for you", "Explore premium profiles", "People you may know") on a profile page | working |
get_inbox | List recent conversations from the LinkedIn messaging inbox | working |
get_conversation | Read a specific messaging conversation by username or thread ID | [#434](https://github.com/stickerdaniel/linkedin-mcp-server/issues/434) |
search_conversations | Search messages by keyword | working |
send_message | Send 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) |
get_company_profile | Extract 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 | working |
get_company_posts | Get recent posts from a company's LinkedIn feed | working |
search_companies | Search for companies on LinkedIn by keywords | working |
get_company_employees | List employees at a company from the /people/ page, with optional keyword filter | working |
search_jobs | Search for jobs with keywords and location filters | working |
search_people | Search for people by keywords, location, connection degree (1st/2nd/3rd), and current company | working |
get_job_details | Get detailed information about a specific job posting | working |
get_feed | Get recent posts from the authenticated user's home feed | working |
close_session | Close browser session and clean up resources | working |
<br/> <br/>
Prerequisites: Install uv.
Client Configuration
{
"mcpServers": {
"linkedin": {
"command": "uvx",
"args": ["linkedin-scraper-mcp@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.
[!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 linkedin-scraper-mcp@latest --login.
<details> <summary><b>🔧 Configuration</b></summary>
Transport Modes:
stdioCLI Options:
--login - Open browser to log in and save persistent profile--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.--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)Basic Usage Examples:
```bash
<details> <summary><b>❗ Troubleshooting</b></summary>
First-time setup behavior:
~/.linkedin-mcp/patchright-browsers/Login issues:
--loginuvx linkedin-scraper-mcp@latest --login which opens a browser where you can solve captchas manually. See the uvx setup for prerequisites.Timeout issues:
--timeout 10000 or TIMEOUT=10000 (milliseconds, default 5000).--tool-timeout 300 or TOOL_TIMEOUT=300 (seconds, default 180).</details>
<br/> <br/>
Prerequisites: Make sure you have Docker installed and running, and uv installed on the host for the one-time --login step.
<details> <summary><b>🔧 Configuration</b></summary>
Transport Modes:
stdioCLI 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.--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]--loginand--no-headlessare 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:
@modelcontextprotocol/inspectorStreamable HTTP as Transport TypeURL to http://localhost:8080/mcp</details>
<details> <summary><b>❗ Troubleshooting</b></summary>
Docker issues:
docker psLogin issues:
--loginuvx linkedin-scraper-mcp@latest --login which opens a browser where you can solve captchas manually. See the uvx setup for prerequisites.Timeout issues:
--timeout 10000 or TIMEOUT=10000 (milliseconds, default 5000).--tool-timeout 300 or TOOL_TIMEOUT=300 (seconds, default 180).Custom Chrome path:
--chrome-path /path/to/chromeCHROME_PATH=/path/to/chrome</details>
<br/> <br/>
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.
```bash
curl -LsSf https://astral.sh/uv/install.sh | sh
uv run pre-commit install
<details> <summary><b>🔧 Configuration</b></summary>
CLI Options:
--login - Open browser to log in and save persistent profile--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 helpNote: 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": {
"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:
--login--login command opens a browser where you can solve it manually.Scraping issues:
--no-headless to see browser actions and debug scraping problems--log-level DEBUG to see more detailed loggingSession issues:
~/.linkedin-mcp/profile/--logout to clear the profile and start freshPython/Patchright issues:
python --version (should be 3.12+)uv run patchright install chromiumuv sync --reinstallTimeout issues:
--timeout 10000 or TIMEOUT=10000 (milliseconds, default 5000).--tool-timeout 300 or TOOL_TIMEOUT=300 (seconds, default 180).Custom Chrome path:
--chrome-path /path/to/chromeCHROME_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. That said, LinkedIn's TOS prohibit automated tools. With normal usage (not bulk scraping!) you're not risking a ban. So far, no users have been banned for using this MCP. If you encounter any issues, let me know in the Discussions. What if my agents execute too many actions? LinkedIn may send you a warning about automated tool usage. If that happens, reduce your automation volume. This MCP executes tool calls sequentially via a queue but has no built-in rate limits. Prompt your agents responsibly.
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。
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。
✅ 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。
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。
| 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 |
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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