linkedin-mcp

linkedin-mcp

Automates LinkedIn job search and Easy Apply using Playwright and Claude Code, with tools for login, job search, form filling, and batch applications.

Category
访问服务器

README

linkedin-mcp

An MCP server that automates LinkedIn job search and Easy Apply using Playwright + Claude Code. Search for jobs matching your skill set, auto-fill application forms from your profile, and track applications in a local database — all from a Claude conversation.

What it does

Tool Description
linkedin_login Open a browser to log in to LinkedIn. Run once — session is saved.
search_jobs Search LinkedIn jobs with smart scoring against your resume skills.
get_job_details Fetch the full job description from a LinkedIn job URL.
easy_apply_poc Inspect a job's Easy Apply form fields without submitting.
easy_apply_submit Navigate all form steps, fill from your profile, and submit.
batch_easy_apply Search + apply to multiple jobs in one go, with dry-run safety.

Prerequisites

  • Python 3.11+
  • Claude Code (or any MCP-compatible client)
  • A LinkedIn account

Setup

1. Clone and install dependencies

git clone https://github.com/Shrushti8/linkedin-mcp.git
cd linkedin-mcp
pip install -r requirements.txt
playwright install chromium

2. Create your credentials file

cp .env.example .env
# Edit .env and fill in your LinkedIn email, password, and resume path

3. Create your profile

Run the interactive setup script — it asks you all the questions and generates profile.json:

python setup.py

Or copy profile.template.json to profile.json and fill it in manually.

profile.json is gitignored and stays local to your machine.

4. Add the MCP server to Claude Code

Add this to your claude_desktop_config.json (or Claude Code MCP settings):

{
  "mcpServers": {
    "linkedin": {
      "command": "python",
      "args": ["/absolute/path/to/linkedin-mcp/server.py"]
    }
  }
}

5. Log in to LinkedIn

In a Claude conversation, call the linkedin_login tool. A browser window opens — log in manually (or it auto-fills if you set LINKEDIN_EMAIL/LINKEDIN_PASSWORD in .env). Your session is saved to the session/ folder for all future calls.

Usage examples

Search for jobs:

search_jobs(keywords="Senior Data Engineer", days=1, easy_apply_only=true)

Inspect a form before applying:

easy_apply_poc(url="https://www.linkedin.com/jobs/view/1234567890")

Apply to a single job (dry run first):

easy_apply_submit(url="...", dry_run=true)
easy_apply_submit(url="...", dry_run=false)

Batch apply to top 5 Easy Apply jobs:

batch_easy_apply(limit=5, keywords="Data Engineer", days=1)

How job scoring works

Each job gets a resume_score based on how many keywords from your resume_score_weights (in profile.json) appear in the job title and description. Big-name companies get a +3 bonus. Results are sorted by score descending.

You can tune the weights in profile.json to match your own skill set.

How form filling works

easy_apply_submit uses a longest-keyword-match approach against your profile.json:

  • Text fields are matched by label (e.g. "years of python experience" → your Python YOE)
  • Salary/CTC fields use your current_ctc_lpa and expected_ctc_lpa
  • Yes/No questions are reasoned about using your notice period, bond preference, relocation preference, and skills you don't have
  • Jobs with questions the tool can't answer are returned in needs_user_input — never submitted blind

Privacy

Your personal data (profile.json, .env, session/, applications.db) is gitignored and never committed. See .gitignore.

Troubleshooting

Tool behavior didn't change after editing a file?
The MCP server loads Python once at startup. After any code edit, reconnect the server: in Claude Code, go to /mcp → linkedin → Reconnect.

Redirected to login page during search?
Your session expired. Run linkedin_login again to refresh it.

profile.json not found warning?
Run python setup.py to create your profile.

推荐服务器

Baidu Map

Baidu Map

百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。

官方
精选
JavaScript
Playwright MCP Server

Playwright MCP Server

一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。

官方
精选
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。

官方
精选
本地
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。

官方
精选
本地
TypeScript
VeyraX

VeyraX

一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。

官方
精选
本地
graphlit-mcp-server

graphlit-mcp-server

模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。

官方
精选
TypeScript
Kagi MCP Server

Kagi MCP Server

一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。

官方
精选
Python
e2b-mcp-server

e2b-mcp-server

使用 MCP 通过 e2b 运行代码。

官方
精选
Neon MCP Server

Neon MCP Server

用于与 Neon 管理 API 和数据库交互的 MCP 服务器

官方
精选
Exa MCP Server

Exa MCP Server

模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。

官方
精选