Install
$ agentstack add mcp-felipfr-linkedin-mcpserver ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ● Network access Used
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
🌐 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](LICENSE) file for details.
Source & license
This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: felipfr
- Source: felipfr/linkedin-mcpserver
- License: MIT
Install and usage instructions live in the source repository linked above.
Reviews
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Versions
- v0.1.0 Imported from the upstream source.