About Linkedin Mcpserver
Linkedin Mcpserver is an MCP server published by felipfr in the Developer Tools category: a powerful Model Context Protocol server for LinkedIn API integration.
The repository has 91 stars and 33 forks, with the last commit a year ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues before depending on it in production.
Install
git clone https://github.com/felipfr/linkedin-mcpserverThis server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.
Tools (7)
get-connectionsRetrieve the current user connections
Parameters not published.
get-my-profileRetrieve the current user
Parameters not published.
get-network-statsRetrieve network statistics for the current user
Parameters not published.
get-profileRetrieve detailed LinkedIn profile information
Parameters not published.
search-jobsSearch for LinkedIn job postings based on various criteria
Parameters not published.
search-peopleSearch for LinkedIn profiles based on various criteria
Parameters not published.
send-messageSend a message to a LinkedIn connection
Parameters not published.
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Security checks
Static checks derived from the repository 5 hours ago. Heuristics on the source, not an audit.
- ✓README presentThe repository ships documentation.
- ✓License declaredUsable under a stated license.
- !Tests presentNo tests found. Behaviour changes may go unnoticed between versions.
- ✓Dependencies pinnedA lockfile pins dependency versions.
- ✓No dynamic code executionSource scan found no eval, dynamic Function, or shell execution.
- !Scoped permissionsDoesn't declare a permission scope. Assume it can do anything its process can.
Releases
README
🌐 LinkedIn MCP Server
A powerful Model Context Protocol server for LinkedIn API integration
📋 Overview
LinkedIn MCP Server brings the power of the LinkedIn API to your AI assistants through the Model Context Protocol (MCP). This TypeScript server empowers AI agents to interact with LinkedIn data, search profiles, find jobs, and even send messages.
MCP (Model Context Protocol) is an open protocol that standardizes how applications provide context to LLMs - think of it as a USB-C port for AI applications, connecting models to external data sources and tools.
✨ Features
🔍 LinkedIn API Tools
- Profile Search - Find LinkedIn profiles with advanced filters
- Profile Retrieval - Get detailed information about LinkedIn profiles
- Job Search - Discover job opportunities with customized criteria
- Messaging - Send messages to LinkedIn connections
- Network Stats - Access connection statistics and analytics
🛠️ Technical Highlights
- TypeScript - Built with modern TypeScript for type safety and developer experience
- Dependency Injection - Uses TSyringe for clean, testable architecture
- Structured Logging - Comprehensive logging with Pino for better observability
- MCP Integration - Implements the Model Context Protocol for seamless AI assistant connectivity
- REST Client - Axios-powered API client with automatic token management
🚀 Development
Prerequisites
- Node.js 20+
- npm/yarn
Setup
# Install dependencies
npm install
# Run the development server
npm run start:dev
# Build the server
npm run build
📦 Installation
To use with Claude Desktop or other MCP-compatible AI assistants:
Configuration
-
macOS:
~/Library/Application Support/Claude/claude_desktop_config.json -
Windows:
%APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"linkedin-mcp-server": {
"command": "/path/to/linkedin-mcp-server/build/index.js"
}
}
}
🔧 Debugging
MCP servers communicate over stdio which can make debugging challenging. Use the integrated MCP Inspector:
# Debug with MCP Inspector
npm run inspector
The Inspector provides a browser-based interface for monitoring requests and responses.
🔒 Security
This server handles sensitive LinkedIn authentication credentials. Review the token management system to ensure it meets your security requirements.
📜 License
This project is licensed under the MIT License. See the LICENSE file for details.
README fetched from the repository 5 hours ago. The original is authoritative.