mcp-server-linkedin

<h1 align="center">LinkedIn MCP Server</h1>

<p align="center"> <a href="https://pypi.org/project/mcp-server-linkedin/"><img src="https://img.shields.io/pypi/v/mcp-server-linkedin.svg" alt="PyPI"></a> <a href="https://www.python.org/downloads/"><img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="Python 3.10+"></a> <a href="LICENSE"><img src="https://img.shields.io/badge/License-MIT-green.svg" alt="License: MIT"></a> <a href="https://modelcontextprotocol.io"><img src="https://img.shields.io/badge/MCP-compatible-purple.svg" alt="MCP"></a> <a href="https://github.com/astral-sh/ruff"><img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json" alt="Ruff"></a> </p>

<p align="center"> <img src="assets/banner.png" alt="LinkedIn MCP Server — Plug AI into LinkedIn" width="600" /> </p>

<p align="center"> <strong>Publish posts, images, videos, and articles to LinkedIn from any AI agent.</strong><br> Works with Claude, Cursor, Kiro, VS Code Copilot, Windsurf, and more. </p>

---

Use Cases

• Content Publishing: Draft and publish LinkedIn posts from your AI assistant without switching context.
• Media Sharing: Upload images and videos alongside your posts in a single command.
• Link Previews: Share articles with auto-generated link preview cards.
• Multi-Format Workflow: Compose text-only updates, visual content, or article shares through one unified interface.
• Account Management: Authenticate, check your profile, and manage your session without leaving your editor.

Built for developers and content creators who want their AI tools to publish directly to LinkedIn.

---

Quick Start

Prerequisites

1. Python 3.10+
2. LinkedIn App — Follow the step-by-step setup guide or the quick version below:
   • Create an app at LinkedIn Developer Portal
   • Products: "Share on LinkedIn" + "Sign In with LinkedIn using OpenID Connect"
   • OAuth 2.0 scopes: openid, profile, email, w_member_social
   • Redirect URL: http://localhost:3000/callback

Install

uvx mcp-server-linkedin

Or with pip:

pip install mcp-server-linkedin

---

Configuration

Set these environment variables:

LINKEDIN_CLIENT_ID=your_client_id        # From LinkedIn Developer Portal
LINKEDIN_CLIENT_SECRET=your_secret_here  # From LinkedIn Developer Portal
LINKEDIN_REDIRECT_URI=http://localhost:3000/callback  # Optional, this is the default

Claude Desktop

Add to your claude_desktop_config.json:

<details> <summary>macOS: ~/Library/Application Support/Claude/claude_desktop_config.json</summary>

{
  "mcpServers": {
    "linkedin": {
      "command": "uvx",
      "args": ["mcp-server-linkedin"],
      "env": {
        "LINKEDIN_CLIENT_ID": "your_client_id",
        "LINKEDIN_CLIENT_SECRET": "your_secret_here"
      }
    }
  }
}

</details>

<details> <summary>Windows: %APPDATA%\Claude\claude_desktop_config.json</summary>

{
  "mcpServers": {
    "linkedin": {
      "command": "uvx",
      "args": ["mcp-server-linkedin"],
      "env": {
        "LINKEDIN_CLIENT_ID": "your_client_id",
        "LINKEDIN_CLIENT_SECRET": "your_secret_here"
      }
    }
  }
}

</details>

VS Code + Copilot

Add to .vscode/mcp.json in your workspace:

{
  "servers": {
    "linkedin": {
      "command": "uvx",
      "args": ["mcp-server-linkedin"],
      "env": {
        "LINKEDIN_CLIENT_ID": "your_client_id",
        "LINKEDIN_CLIENT_SECRET": "your_secret_here"
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json in your project root:

{
  "mcpServers": {
    "linkedin": {
      "command": "uvx",
      "args": ["mcp-server-linkedin"],
      "env": {
        "LINKEDIN_CLIENT_ID": "your_client_id",
        "LINKEDIN_CLIENT_SECRET": "your_secret_here"
      }
    }
  }
}

Kiro

Add to .kiro/settings/mcp.json:

{
  "mcpServers": {
    "linkedin": {
      "command": "uvx",
      "args": ["mcp-server-linkedin"],
      "env": {
        "LINKEDIN_CLIENT_ID": "your_client_id",
        "LINKEDIN_CLIENT_SECRET": "your_secret_here"
      }
    }
  }
}

Claude Code

claude mcp add linkedin -- uvx mcp-server-linkedin

Then set LINKEDIN_CLIENT_ID and LINKEDIN_CLIENT_SECRET in your environment.

Windsurf

Add to your Windsurf MCP configuration:

{
  "mcpServers": {
    "linkedin": {
      "command": "uvx",
      "args": ["mcp-server-linkedin"],
      "env": {
        "LINKEDIN_CLIENT_ID": "your_client_id",
        "LINKEDIN_CLIENT_SECRET": "your_secret_here"
      }
    }
  }
}

Running from Source

Replace "command": "uvx", "args": ["mcp-server-linkedin"] with:

{
  "command": "uv",
  "args": ["--directory", "/path/to/mcp-server-linkedin", "run", "mcp-server-linkedin"]
}

---

Authentication

1. Start your MCP client (Claude Desktop, Kiro, etc.)
2. Ask: "Authenticate with LinkedIn"
3. Browser opens → authorize the app → callback captured automatically
4. Token saved to ~/.mcp-server-linkedin/token.json
5. Token lasts 2 months. Re-run linkedin_auth when it expires.

---

Tools

Tool	Description
linkedin_auth	OAuth 2.0 browser-based authentication
linkedin_get_profile	Get your name, email, and person URN
linkedin_logout	Remove stored token
linkedin_post_text	Publish a text-only post
linkedin_post_image	Publish a post with an image
linkedin_post_video	Publish a post with a video (up to 200 MB)
linkedin_post_article	Publish a post with a link preview
linkedin_delete_post	Delete a post by ID
linkedin_get_post_stats	Get post analytics (requires Community Management API)
linkedin_get_all_stats	Get aggregated analytics (requires Community Management API)

Tool Details

<details> <summary><b>linkedin_post_text</b></summary>

Parameter	Type	Default	Description
text	string	required	Post content (up to ~3000 chars)
visibility	string	"PUBLIC"	"PUBLIC" or "CONNECTIONS"

</details>

<details> <summary><b>linkedin_post_image</b></summary>

Parameter	Type	Default	Description
text	string	required	Post caption
image_path	string	required	Absolute path to image (JPEG, PNG, GIF)
visibility	string	"PUBLIC"	"PUBLIC" or "CONNECTIONS"

</details>

<details> <summary><b>linkedin_post_video</b></summary>

Parameter	Type	Default	Description
text	string	required	Post caption
video_path	string	required	Absolute path to video (MP4, max 200 MB)
visibility	string	"PUBLIC"	"PUBLIC" or "CONNECTIONS"

</details>

<details> <summary><b>linkedin_post_article</b></summary>

Parameter	Type	Default	Description
text	string	required	Post commentary
url	string	required	Article URL (generates link preview)
title	string	""	Optional link preview title
description	string	""	Optional link preview description
visibility	string	"PUBLIC"	"PUBLIC" or "CONNECTIONS"

</details>

<details> <summary><b>linkedin_delete_post</b></summary>

Parameter	Type	Default	Description
post_id	string	required	Post URN (e.g., urn:li:ugcPost:123456)

</details>

---

Architecture

src/mcp_server_linkedin/
├── config.py            # Constants, API URLs, settings dataclass
├── exceptions.py        # Typed exception hierarchy
├── server.py            # FastMCP entrypoint + tool registration
├── models/              # Frozen dataclass API response models
├── services/            # Async API client with connection pooling
├── tools/               # MCP tool implementations (validate → delegate → format)
│   ├── auth.py          # OAuth flow, profile, logout
│   ├── posting.py       # Text, image, video, article, delete
│   └── analytics.py     # Stubbed (pending API access)
└── utils/               # Token persistence

---

Rate Limits

Limit	Value
API requests per member per day	150
Token duration	2 months
Max video file size	200 MB

The server relays LinkedIn's rate limit errors clearly but does not enforce limits internally.

---

Security

• Tokens stored locally at ~/.mcp-server-linkedin/token.json
• No credentials in code — all secrets via environment variables
• Official API only — uses w_member_social scope
• Local OAuth callback — authorization code never leaves your machine
• No data collection — this server sends nothing except LinkedIn API calls

---

Development

git clone https://github.com/Huzaifa-ali/mcp-server-linkedin.git
cd mcp-server-linkedin
uv sync --all-extras
pre-commit install

uv run mcp-server-linkedin                    # Run the server
uv run ruff check src/                        # Lint
uv run ruff format src/                       # Format
uv run mypy src/                              # Type check
uv run pytest                                 # Test

Test with MCP Inspector:

npx @modelcontextprotocol/inspector uv run mcp-server-linkedin

---

Contributing

See CONTRIBUTING.md for guidelines. In short:

1. Fork the repo and create a feature branch
2. Make your changes with type hints and docstrings
3. Run pre-commit run --all-files (must pass)
4. Open a pull request

---

License

MIT — see LICENSE.