LinkedIn MCP Server

AI-powered LinkedIn content creation, analytics, and engagement. Create posts, analyze performance, manage drafts, and grow your professional presence—all through natural conversation with Claude.

A Model Context Protocol (MCP) server that connects Claude to LinkedIn for content creation, scheduling, and analytics.

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✅ What's Working (Tested & Verified)

Content Creation (Official API)

Capability	Example Prompt	Status
Create Posts	"Create a LinkedIn post about AI trends"	✅ Working
Image Posts	"Post this image with a caption about our launch"	✅ Working
Create Polls	"Create a poll asking about favorite programming languages"	✅ Working
Delete Posts	"Delete my last post"	✅ Working
Get My Profile	"Show me my LinkedIn profile"	✅ Working

Content Planning (Local Features)

Capability	Example Prompt	Status
Draft Content	"Save this as a draft for later"	✅ Working
List Drafts	"Show my saved drafts"	✅ Working
Publish Drafts	"Publish my 'Product Launch' draft"	✅ Working
Schedule Posts	"Schedule this post for Tuesday at 9am"	✅ Working
Manage Schedule	"Show my scheduled posts"	✅ Working
Content Analysis	"Analyze this draft and suggest improvements"	✅ Working

Profile Viewing (Browser Automation)

Capability	Example Prompt	Status
View Profiles	"Look up Bill Gates on LinkedIn"	⚠️ Limited (browser fallback)

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⚠️ Known Limitations

LinkedIn actively blocks unofficial API access. The following features are currently unreliable due to LinkedIn's bot detection:

• ❌ Search (people/companies)
• ❌ Connection management
• ❌ Feed browsing
• ❌ Messaging
• ❌ Network statistics
• ❌ Company research

These use the tomquirk/linkedin-api library which LinkedIn frequently blocks. We're exploring alternatives.

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Quick Start

Prerequisites

• Python 3.11+
• uv (recommended) or pip
• LinkedIn account
• LinkedIn Developer App (free, 5 min setup)

Step 1: Clone and Install

git clone https://github.com/southleft/linkedin-mcp.git
cd linkedin-mcp

# Install with uv (recommended)
uv venv && source .venv/bin/activate
uv pip install -e .

# Install browser automation (optional, for profile viewing)
playwright install chromium

Step 2: Create LinkedIn Developer App

1. Go to LinkedIn Developer Portal
2. Click "Create app"
3. Fill in the details:
   • App name: e.g., "My LinkedIn MCP"
   • LinkedIn Page: Select or create a company page
   • Privacy policy URL: Your website or LinkedIn profile
   • App logo: Any 100x100 image
4. Go to "Products" tab → Request "Share on LinkedIn" (instant approval)
5. Go to "Auth" tab:
   • Copy Client ID and Client Secret
   • Add redirect URL: http://localhost:8765/callback

Step 3: Configure Environment

Create a .env file:

# LinkedIn OAuth Credentials (Required)
LINKEDIN_CLIENT_ID=your_client_id_here
LINKEDIN_CLIENT_SECRET=your_client_secret_here

# Enable API features
LINKEDIN_API_ENABLED=true

Step 4: Authenticate

# OAuth authentication (opens browser, required for posting)
linkedin-mcp-auth oauth

# Extract browser cookies (optional, for additional features)
linkedin-mcp-auth extract-cookies --browser chrome

# Verify status
linkedin-mcp-auth status

Step 5: Connect to Claude

Claude Code (Recommended)

Add to ~/.claude.json:

{
  "mcpServers": {
    "linkedin-mcp": {
      "type": "stdio",
      "command": "/path/to/python3",
      "args": ["-m", "linkedin_mcp"],
      "cwd": "/path/to/linkedin-mcp",
      "env": {
        "LINKEDIN_API_ENABLED": "true",
        "PYTHONPATH": "/path/to/linkedin-mcp/src"
      }
    }
  }
}

Then run /mcp in Claude Code to connect.

Claude Desktop

Add to your config file:

Platform	Config Location
macOS	~/Library/Application Support/Claude/claude_desktop_config.json
Windows	%APPDATA%\Claude\claude_desktop_config.json
Linux	~/.config/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "linkedin": {
      "command": "/path/to/linkedin-mcp/.venv/bin/python",
      "args": ["-m", "linkedin_mcp"],
      "cwd": "/path/to/linkedin-mcp",
      "env": {
        "LINKEDIN_CLIENT_ID": "your_client_id",
        "LINKEDIN_CLIENT_SECRET": "your_client_secret",
        "LINKEDIN_API_ENABLED": "true"
      }
    }
  }
}

Restart Claude Desktop after updating.

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Available Tools

✅ Reliable Tools (Official API + Local)

Profile

Tool	Description
get_my_profile()	Get your LinkedIn profile
get_auth_status()	Check authentication status

Content Creation

Tool	Description
create_post(text, visibility)	Create a text post
create_image_post(text, image_path)	Create a post with image
create_poll(question, options)	Create a poll
delete_post(post_urn)	Delete a post

Drafts & Scheduling

Tool	Description
create_draft(content, title, tags)	Save content for later
list_drafts()	List all drafts
get_draft(draft_id)	Get a specific draft
update_draft(draft_id, ...)	Update a draft
delete_draft(draft_id)	Delete a draft
publish_draft(draft_id)	Publish a draft
schedule_post(content, time)	Schedule for future
list_scheduled_posts()	View scheduled posts
cancel_scheduled_post(job_id)	Cancel scheduled post
update_scheduled_post(job_id, ...)	Update scheduled post

Content Analysis

Tool	Description
analyze_draft_content(content)	Get improvement suggestions

⚠️ Limited Tools (May Be Blocked)

These tools use the unofficial API and may fail due to LinkedIn's bot detection:

Tool	Description	Fallback
get_profile(id)	Get any profile	Browser automation
search_people(keywords)	Search for people	None
search_companies(keywords)	Search for companies	None
get_connections(limit)	List connections	None
get_feed(limit)	Browse feed	None
get_network_stats()	Network analysis	None
send_message(id, text)	Send DM	None
get_company(id)	Company details	None

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Example Conversations

Content Creator Workflow (✅ Reliable)

You: "I want to post about continuous learning in tech"

Claude: I'll help you create that post. Here's a draft:

"🚀 In tech, the day you stop learning is the day you start falling behind.

Whether it's a new framework or a completely new domain—curiosity is our greatest competitive advantage.

What are you learning this week? 👇

#ContinuousLearning #TechCareers #GrowthMindset"

Should I post this publicly or save it as a draft?

Content Planning (✅ Reliable)

You: "Save this as a draft for my product launch next week"

Claude: Done! I've saved your draft titled "Product Launch" with tags: product, launch, announcement.

Would you like me to:
- Schedule it for a specific time?
- Analyze it for engagement potential?
- Show you all your drafts?

Post Scheduling (✅ Reliable)

You: "Schedule my launch post for Tuesday at 9am Central"

Claude: ✅ Scheduled! Your post will go live:
- Date: Tuesday, January 7, 2025
- Time: 9:00 AM Central
- Visibility: Public

You can view or cancel scheduled posts anytime.

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CLI Commands

# Authentication
linkedin-mcp-auth status              # Check auth status
linkedin-mcp-auth oauth               # OAuth flow (opens browser)
linkedin-mcp-auth oauth --force       # Force re-authentication
linkedin-mcp-auth extract-cookies     # Extract session cookies
linkedin-mcp-auth logout --all        # Clear all credentials

# Run Server
linkedin-mcp                          # Start MCP server

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Environment Variables

Variable	Default	Description
LINKEDIN_CLIENT_ID	-	OAuth Client ID (required)
LINKEDIN_CLIENT_SECRET	-	OAuth Client Secret (required)
LINKEDIN_API_ENABLED	false	Enable API features
MCP_TRANSPORT	stdio	Transport: stdio, streamable-http
MCP_HOST	127.0.0.1	HTTP server host
MCP_PORT	8000	HTTP server port
LOG_LEVEL	INFO	Logging level

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Troubleshooting

"LinkedIn client not initialized"

linkedin-mcp-auth status    # Check what's configured
linkedin-mcp-auth oauth     # Re-authenticate

"Exceeded 30 redirects" or "RetryError"

LinkedIn is blocking API access. This is common with the unofficial API. Solutions:

1. Refresh cookies: linkedin-mcp-auth extract-cookies --browser chrome
2. Wait and retry later
3. Use official API tools (posting, drafts, scheduling)

"Application context not initialized"

Reconnect the MCP server: Run /mcp in Claude Code.

Posts not appearing

• Ensure OAuth is authenticated: linkedin-mcp-auth status
• Check your Developer App has "Share on LinkedIn" product enabled

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Security

• OAuth tokens: Stored securely in system keychain
• Session cookies: Stored in system keychain (never transmitted)
• Credentials: Loaded from environment variables
• No data collection: Everything runs locally

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Development

# Install dev dependencies
uv pip install -e ".[dev]"

# Run tests
pytest tests/ -v

# Linting
ruff check src/ && ruff format src/

# Type checking
mypy src/linkedin_mcp

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License

MIT License - see LICENSE for details.

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Acknowledgments

• tomquirk/linkedin-api - LinkedIn API library
• FastMCP - MCP SDK for Python
• Model Context Protocol - AI tool protocol

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