LinkedIn Custom MCP Server

Empower your AI agents with professional networking capabilities.

This project implements a Model Context Protocol (MCP) server that acts as a bridge between Large Language Models (LLMs) like Claude or Gemini and the LinkedIn platform. It allows your AI assistants to autonomously manage your professional presence, interact with your feed, search for opportunities, and analyze profiles—all through a secure and authenticated interface.

Built with performance and modularity in mind using FastMCP and Python.

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🌟 Key Features

• 📈 Feed Management: Create text posts, upload images, and manage comments seamlessly.
• 👤 Profile Intelligence: Retrieve and analyze your own profile or public member profiles.
• 🤝 Network Interaction: Engage with content by commenting on posts and shares.
• 🏢 Company Insights: Search for companies and retrieve detailed organizational data.
• 💼 Job Search: Find relevant job postings based on keywords and location.
• 🔐 Secure Auth: Robust OAuth 2.0 implementation with token persistence.

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📂 Project Structure

LinkedIn_mcp_custom_server/
├── main.py              # Server entry point & tool registration
├── config.py            # Environment & settings management
├── utils.py             # Shared API & error handling helpers
├── requirements.txt     # Python dependencies
├── .env                 # Local secrets (not committed)
├── .gitignore           # Git exclusion rules
├── LICENSE              # MIT License details
└── tools/               # Modular tool implementations
    ├── auth.py          # OAuth 2.0 flow logic
    ├── profile.py       # Profile data extraction
    ├── post.py          # Posts, Comments, and Image uploads
    ├── company.py       # Company search and profiles
    ├── job.py           # Job search and details
    └── search.py        # People search and member profiles

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🚀 Installation & Setup

Prerequisites

• Python 3.12+ installed on your system.
• A LinkedIn Developer App (See configuration below).

Step 1: Clone the Repository

git clone https://github.com/SARAMALI15792/LinkedIn_mcp_custom_server.git
cd LinkedIn_mcp_custom_server

Step 2: Install Dependencies

We recommend using a virtual environment.

# Create and activate virtual environment (Windows)
python -m venv .venv
.venv\Scripts\activate

# Install requirements
pip install -r requirements.txt

Step 3: Configure Environment

1. Go to the LinkedIn Developer Portal.
2. Create a new app and request access to the "Sign In with LinkedIn using OpenID Connect" and "Share on LinkedIn" products.
3. In the Auth tab, add http://localhost:8000 to the Authorized redirect URLs.
4. Create a .env file in the project root:

LINKEDIN_CLIENT_ID=your_client_id
LINKEDIN_CLIENT_SECRET=your_client_secret
LINKEDIN_REDIRECT_URI=http://localhost:8000
# Access token will be added automatically after login

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🏃‍♂️ Usage

Starting the Server

Run the server locally using Python:

python main.py

The server will start listening on http://127.0.0.1:8000 using the SSE (Server-Sent Events) transport.

Connecting to an MCP Client

To use this with Claude Desktop, add the following to your config file (%APPDATA%\Claude\claude_desktop_config.json on Windows):

{
  "mcpServers": {
    "linkedin": {
      "command": "C:/path/to/project/.venv/Scripts/python.exe",
      "args": ["C:/path/to/project/main.py"]
    }
  }
}

First-Time Authentication

1. Ask your Agent: "Generate a LinkedIn login URL."
2. Open the provided link and authorize the app.
3. You will be redirected to a page. Copy the code parameter from the URL bar.
4. Ask your Agent: "Exchange this code for a token: [PASTE_CODE]"
5. You are now connected!

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💡 Usage Examples

Once connected, you can ask your AI agent to perform various tasks:

📝 Posting Content

"Create a LinkedIn post with the text 'Excited to launch my new MCP server!' and set visibility to CONNECTIONS." "Post this image 'C:/photos/launch.jpg' with the caption 'Project Launch Day!'"

🔎 Job Hunting

"Search for 'Senior Python Developer' jobs in 'San Francisco' and show me the top 3 details."

📊 Profile & Network

"Get my profile summary." "Who is the user with the username 'stickerdaniel'?"

💬 Engagement

"Show me the comments on my latest post." "Reply to the first comment saying 'Thanks for the support!'"

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🛠️ Available Tools

Category	Tool Name	Description
Auth	linkedin_get_oauth_url	Generate the OAuth 2.0 authorization URL for LinkedIn login.
	linkedin_exchange_code	Exchange an authorization code for a persistent access token.
Profile	linkedin_get_my_profile	Retrieve your own profile information (Name, Email, Picture).
	linkedin_get_member_profile	Fetch public profile details for a specific member using their URN.
Search	linkedin_search_people	Search for LinkedIn members based on keywords and filters.
Post	linkedin_create_post	Publish a text-only update to your professional LinkedIn feed.
	linkedin_create_image_post	Upload an image and publish a media post to your feed.
	linkedin_update_post	Update a post's content (via the Delete & Re-create method).
	linkedin_delete_post	Permanently remove a post from your feed using its URN.
	linkedin_get_recent_posts	Retrieve a list of your most recent activity and publications.
Comment	linkedin_create_comment	Post a new comment on a share, article, or video.
	linkedin_get_post_comments	List all comments and reactions for a specific post.
	linkedin_delete_comment	Remove a comment you previously published.
Company	linkedin_search_companies	Find organizational profiles using keywords or industries.
	linkedin_get_company_profile	Retrieve detailed information about a specific company.
Job	linkedin_search_jobs	Find open career opportunities by keywords and location.
	linkedin_get_job_details	Get the full description and application details for a job.

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🤝 Contribution Guidelines

We welcome contributions to make this server even better!

1. Fork the Repository: Click the "Fork" button on GitHub.
2. Create a Branch: git checkout -b feature/amazing-feature.
3. Commit Changes: git commit -m 'Add amazing feature'.
4. Push to Branch: git push origin feature/amazing-feature.
5. Open a Pull Request: Submit your changes for review.

Please ensure your code follows the existing modular structure in the tools/ directory.

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📄 License

This project is open-source and available under the MIT License. See the LICENSE file for full details.