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eliasbiondo/linkedin-mcp-server

Search LinkedIn people, companies and jobs

装之前:没有可直接复制的命令 · 许可证未标注 · 链接可访问

第一步:git clone https://github.com/eliasbiondo/linkedin-mcp-server.git

在 GitHub 查看 ↗链接已于 2026-11-12 核查 · HTTP 200 · 打开的是厂商自己的官网
安装与配置
客户端配置(取自该仓库的安装命令)
{
  "mcpServers": {
    "eliasbiondo-linkedin-mcp-server": {
      "command": "npx",
      "args": ["@modelcontextprotocol/inspector"]
    }
  }
}

解析自我们于 2026-11-07 抓取的该仓库 README;我们未执行过。

command/args 来自仓库写明的安装命令;不确定时请以该项目 README 为准。
VS Code(.vscode/mcp.json —— 键名是 servers)
{
  "servers": {
    "eliasbiondo-linkedin-mcp-server": {
      "command": "npx",
      "args": ["@modelcontextprotocol/inspector"]
    }
  }
}
VS Code 顶层键是 <code>servers</code>,其余与上面那份相同。
Claude Code(命令行)
claude mcp add --transport stdio eliasbiondo-linkedin-mcp-server -- npx @modelcontextprotocol/inspector
Claude Code 不收 JSON 文件,用这条命令直接加。
配置项的键名以你的客户端为准:客户端与 CLI
来源明细
收录自 abordage/awesome-mcp 榜单(我们从中收集的条目之一) · 条目类型:MCP 服务
收录与活跃
收录于 2026-11-05 · 最近见到 2026-11-14 · 共见到 10 次 · 被 10 个来源列出
评分构成
综合分 1,003 · 10 个来源 · mcp
安装
npx @modelcontextprotocol/inspector
常见问题(答案都来自我们的记录)
怎么安装?
该仓库给出的安装命令是 npx @modelcontextprotocol/inspector。我们的记录里它是仓库自己提供的;不保证在你的客户端上直接可用。
它适合谁 / 用来做什么?
我们把它归在这些标签下: MCP 服务。标签来自条目自身,不是我们强加的分类。
谁维护它、还在更新吗?
我们收录于 2026-11-05;最近见到 2026-11-14。这里没有"官方认证"或"质量评级"——我们只记录来源与时间。

# LinkedIn MCP Server

以下摘录自该仓库的 README(片段) · 在 GitHub 读完整 README →

A Model Context Protocol (MCP) server for LinkedIn. Search people, companies, and jobs, scrape profiles, and retrieve structured JSON data from any MCP-compatible AI client.
https://github.com/user-attachments/assets/50cd8629-41ee-4261-9538-40dc7d30294e
Built with FastMCP, Patchright, and a clean hexagonal architecture.
## Features
| Category | Tools |
| People | get_person_profile · search_people |
| Companies | get_company_profile · get_company_posts |
| Jobs | get_job_details · search_jobs |
| Browser | close_browser |
### Person Profile Sections
The get_person_profile tool supports granular section scraping. Request only the sections you need:
Main profile (always included) — name, headline, location, followers, connections, about, profile image
Experience — title, company, dates, duration, description, company logo
Education — school, degree, dates, description, school logo
Contact info — email, phone, websites, birthday, LinkedIn URL
Interests — people, companies, and groups followed
Honors and awards — title, issuer, description
Languages — language name and proficiency level
Posts — recent activity with reactions and timestamps
Recommendations — received and given, with author details
### Company Profile Sections
About (always included) — overview, website, industry, size, headquarters, specialties, logo
Posts — recent feed posts with engagement metrics
Jobs — current open positions
### Job Search Filters
The search_jobs tool supports the following filters:
| Filter | Values |
| date_posted | past_hour, past_24_hours, past_week, past_month |
| job_type | full_time, part_time, contract, temporary, internship, other |
| experience_level | entry, associate, mid_senior, director, executive |
| work_type | on_site, remote, hybrid |
| easy_apply | true / false |
| sort_by | date, relevance |
## Prerequisites
Python 3.12 or later
uv package manager
A LinkedIn account for authentication
## Quick Start
### 1. Clone and install
bash
git clone https://github.com/eliasbiondo/linkedin-mcp-server.git
cd linkedin-mcp-server
uv sync
### 2. Install browser
This project uses Patchright (a patched fork of Playwright) for browser automation. You need to install the browser binaries before first use:
bash
uv run patchright install
> Windows users: If the command above fails with program not found, run instead:
> powershell
> uv run python -m patchright install
### 3. Authenticate with LinkedIn
bash
uv run linkedin-mcp-server --login
A browser window will open. Log in to LinkedIn and the session will be persisted locally at ~/.linkedin-mcp-server/browser-data.
### 4. Run the server
stdio transport (default — for Claude Desktop, Cursor, and similar clients):
bash
uv run linkedin-mcp-server
HTTP transport (for remote clients, the MCP Inspector, etc.):
bash
uv run linkedin-mcp-server --transport streamable-http --host 0.0.0.0 --port 8000
## Client Integration
### Claude Desktop / Cursor
Add to your MCP configuration file:
json
"mcpServers": {
"linkedin": {
"command": "uv",
"args": [
"--directory", "/path/to/linkedin-mcp-server",
"run", "linkedin-mcp-server"
### MCP Inspector
bash
npx @modelcontextprotocol/inspector
Then connect to http://localhost:8000/mcp if using HTTP transport.
收录徽章(可选)
想把收录标记放进 README 就复制这行,可选,不影响收录。
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来源
awesome · https://github.com/eliasbiondo/linkedin-mcp-server
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