AI导哈

领英个人资料编辑 MCP 服务器

linkedit-mcp 是一个 Model Context Protocol (MCP) 服务器，让 AI 助手能够读取和编辑用户的领英个人资料，包括职业头衔、简介、工作经历、教育背景和技能，适用于通过 AI 助手管理职业档案和更新履历信息。

  • by SimbioLabs
  • TypeScript
  • 本地部署
  • 更新于
在 GitHub 查看 SimbioLabs/linkedit-mcp

使用说明

linkedit-mcp

A Model Context Protocol server that lets AI assistants read and edit your LinkedIn profile — headline, about section, work experience, education, and skills.

Built by SimbioLabs.

Tools

Tool Description
authenticate Start OAuth 2.0 flow — opens LinkedIn in your browser
logout Clear stored session tokens
get_profile Read name, headline, about, email, and vanity URL
update_headline Update your LinkedIn headline (max 220 chars)
update_about Update your About / summary section (max 2600 chars)
get_experience List all work experience entries
add_experience Add a new position
update_experience Edit an existing position
delete_experience Remove a position
get_education List all education entries
add_education Add a new education entry
update_education Edit an existing education entry
delete_education Remove an education entry
get_skills List all skills
add_skill Add a skill
remove_skill Remove a skill

Setup

1. Create a LinkedIn Developer App

  1. Go to LinkedIn Developer Portal and create a new app.
  2. Under Auth, add http://localhost:3000/callback as an OAuth 2.0 redirect URL.
  3. Under Products, request access to Sign In with LinkedIn using OpenID Connect (provides r_liteprofile, r_emailaddress).
  4. Copy your Client ID and Client Secret.

Note on profile write access: The update_headline, update_about, add_experience, add_education, and skill tools use LinkedIn's profile write API, which requires your app to have the LinkedIn Partner Program permissions (w_member_social is open, but full profile write requires partner approval). Check LinkedIn API access levels for details.

2. Configure environment

cp .env.example .env

Edit .env with your credentials:

LINKEDIN_CLIENT_ID=your_client_id_here
LINKEDIN_CLIENT_SECRET=your_client_secret_here
LINKEDIN_REDIRECT_URI=http://localhost:3000/callback

3. Install and build

npm install
npm run build

4. Add to Cursor / Claude Desktop

In your MCP config (e.g. ~/.cursor/mcp.json or claude_desktop_config.json):

{
  "mcpServers": {
    "linkedit": {
      "command": "node",
      "args": ["/absolute/path/to/linkedit-mcp/dist/index.js"],
      "env": {
        "LINKEDIN_CLIENT_ID": "your_client_id",
        "LINKEDIN_CLIENT_SECRET": "your_client_secret",
        "LINKEDIN_REDIRECT_URI": "http://localhost:3000/callback"
      }
    }
  }
}

5. Authenticate

In your AI assistant, run:

authenticate

A browser window will open. Approve the LinkedIn permissions, then return to your assistant — you're ready.

Example usage

Update my LinkedIn headline to "Founder @ SimbioLabs | Building AI-native products"

Add a new job: Software Engineer at Acme Corp, Jan 2022 to Mar 2024, describe it as leading backend infrastructure for a B2B SaaS platform

Add my MBA from Stanford Graduate School of Business, 2019–2021

Token storage

Tokens are stored locally at ~/.linkedit-mcp/tokens.json. They are never sent anywhere other than LinkedIn's OAuth endpoints. Use logout to clear them at any time.

Development

npm run dev   # watch mode
npm start     # run compiled server

License

MIT — SimbioLabs

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