How do I use mcp-server-linkedin?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@mcp-server-linkedin Publish a LinkedIn post about our new AI feature with an image" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

mcp-server-linkedin

by Huzaifa-ali

Overview Schema Related Servers Score Discussions

Python

Remote

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

Python 3.10+
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

Related MCP server: LinkedIn MCP Server

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:

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

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

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

Start your MCP client (Claude Desktop, Kiro, etc.)
Ask: "Authenticate with LinkedIn"
Browser opens → authorize the app → callback captured automatically
Token saved to ~/.mcp-server-linkedin/token.json
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

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

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"`

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"`

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"`

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

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:

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

License

MIT — see LICENSE.

Install Server

license - permissive license

quality

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

–Releases (12mo)

Commit activity

Resources

GitHub Repository

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