A powerful Model Context Protocol server for LinkedIn API integration
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"linkedin-mcpserver": {
"command": "<see-readme>",
"args": []
}
}
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A powerful Model Context Protocol server for LinkedIn API integration
No automated test available for this server. Check the GitHub README for setup instructions.
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A powerful Model Context Protocol server for LinkedIn API integration
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.
# Install dependencies
npm install
# Run the development server
npm run start:dev
# Build the server
npm run build
To use with Claude Desktop or other MCP-compatible AI assistants:
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"
}
}
}
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.
This server handles sensitive LinkedIn authentication credentials. Review the token management system to ensure it meets your security requirements.
This project is licensed under the MIT License. See the LICENSE file for details.