linkedit-mcp
Enables AI assistants to read and edit LinkedIn profiles including headline, about section, work experience, education, and skills through OAuth 2.0 authentication.
README
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
- Go to LinkedIn Developer Portal and create a new app.
- Under Auth, add
http://localhost:3000/callbackas an OAuth 2.0 redirect URL. - Under Products, request access to Sign In with LinkedIn using OpenID Connect (provides
r_liteprofile,r_emailaddress). - 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_socialis 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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