linkedin server

The LinkedIn MCP Server exposes a set of MCP-enabled tools that let your AI agents interact with LinkedIn data inside the Model Context Protocol ecosystem. Core capabilities include profile searching with advanced filters, retrieving detailed profile information, discovering job opportunities, sending messages to connections, and accessing network statistics. To use these tools, run the server in your environment and connect an MCP-enabled agent or assistant that can issue context-enabled requests to the server. The server communicates via standard IO for MCP, so it can integrate with typical MCP toolchains and inspectors. You can also use the MCP Inspector to observe requests and responses in a browser-based interface for debugging and observability. When running locally, start the server (for example with npm run start:dev or by executing the built entrypoint) and point your agent at the host/port the MCP server exposes. The tools are designed to be used by your AI agent via MCP tool calls like searchProfile, getProfile, searchJobs, sendMessage, and getNetworkStats, each returning structured results that your agent can present or further process.

Prerequisites:

• Node.js 20+ installed on your system
• npm or yarn for package management

Step-by-step installation:

1. Clone the repository or download the source code
2. Install dependencies npm install
3. Build the server (produces build/index.js or equivalent entrypoint) npm run build
4. Run the development server npm run start:dev
5. (Optional) Run the MCP Inspector for debugging npm run inspector

Configuration tips:

• Ensure any LinkedIn API credentials or tokens are provided via environment variables or a secure config file as required by the server implementation.
• If you deploy, point the runtime to the built entry (build/index.js) or adjust the command accordingly to your deployment environment.

Environment and configuration tips:

• This MCP server handles sensitive LinkedIn credentials. Review token management and storage practices to meet your security requirements.
• If you customize environment-specific endpoints or proxies, ensure CORS and network policies allow your MCP clients to reach the server.
• For production, consider configuring log rotation and structured logging (Pino) to facilitate troubleshooting.
• If you upgrade Node.js, verify compatibility with TypeScript build outputs and dependencies (e.g., TSyringe DI and Axios client).
• Common issues often relate to missing environment variables (e.g., tokens) or incorrect paths to the built entry. Use the MCP Inspector to trace requests when debugging.