Skip to main content
Glama
vikram-agentic

LinkedIn Lead Automation MCP Server

by vikram-agentic
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Hybrid

LinkedIn Lead Automation MCP Server

Production-grade LinkedIn Lead Automation MCP (Model Context Protocol) Server with real-time search, analysis, scoring, messaging, and automated follow-up sequences.

Features

  • 🔍 Lead Discovery: Search LinkedIn profiles by keywords, location, and filters

  • 📊 Profile Analysis: Extract and analyze complete LinkedIn profile data

  • 🎯 AI-Powered Scoring: Intelligent lead scoring (0-100) based on profile data

  • 💬 Message Generation: Hyper-personalized message generation using AI

  • 📨 Automated Messaging: Send connection requests and direct messages

  • 🔄 Follow-up Sequences: Automated multi-stage follow-up campaigns

  • 🔐 API Key Management: Secure tier-based access control

  • 📈 Usage Tracking: Monitor API usage and enforce tier limits

  • 🗄️ PostgreSQL Support: Built with Neon PostgreSQL for production use

Architecture

  • MCP Server (src/index.js): Stdio-based MCP protocol server

  • HTTP API (src/http-server.js): RESTful HTTP API wrapper

  • Background Worker (src/worker.js): Automated follow-up sequence processor

  • Database (src/database-pg.js): PostgreSQL database layer

  • LinkedIn Automation (src/linkedin.js): Chrome DevTools Protocol integration

  • AI Service (src/ai.js): Anthropic Claude integration for scoring and messaging

Prerequisites

  • Node.js 18+

  • PostgreSQL (Neon or any PostgreSQL 14+)

  • Chrome/Chromium browser with remote debugging enabled

  • Anthropic API Key (for AI features)

Installation

# Clone the repository git clone https://github.com/vikram-agentic/linkedin-mcp.git cd linkedin-mcp # Install dependencies npm install # Create .env file cp .env.example .env

Configuration

Create a .env file with the following variables:

# Database (Neon PostgreSQL) DATABASE_URL=postgresql://user:password@host/database?sslmode=require # AI Service (Anthropic) ANTHROPIC_API_KEY=your_anthropic_api_key # Server Configuration PORT=3001 # Chrome DevTools Protocol (optional, for browser automation) CDP_URL=http://localhost:9222

Database Setup

  1. Create a Neon PostgreSQL database (or use any PostgreSQL 14+)

  2. Run the schema in Neon SQL Editor:

# Use schema-neon.sql for Neon PostgreSQL cat database/schema-neon.sql

Copy and paste the SQL from database/schema-neon.sql into Neon SQL Editor and execute it.

Usage

Start MCP Server (Stdio)

npm start

This starts the MCP server using stdio transport. Connect via MCP clients like Claude Desktop.

Start HTTP API Server

npm run http

This starts the HTTP API server on port 3001 (or PORT from .env).

Start Background Worker

npm run worker

This starts the automated follow-up sequence processor.

API Endpoints

Health Check

GET /health

Generate API Key

POST /api/generate-key Body: { "tier": "starter" | "professional" | "agency" | "enterprise" }

Connect Browser

POST /api/browser/connect Body: { "cdp_url": "http://localhost:9222" }

Setup LinkedIn Session

POST /api/session/setup Body: { "api_key": "...", "li_at_cookie": "..." }

Search Leads

POST /api/leads/search Body: { "api_key": "...", "keywords": "...", "location": "...", "limit": 25 }

Analyze Profile

POST /api/leads/analyze Body: { "api_key": "...", "profile_url": "..." }

Score Lead

POST /api/leads/score Body: { "api_key": "...", "profile_url": "..." }

Generate Message

POST /api/messages/generate Body: { "api_key": "...", "profile_url": "...", "value_proposition": "...", "message_type": "connection" | "direct" }

Send Message

POST /api/messages/send Body: { "api_key": "...", "profile_url": "...", "message": "...", "is_connection_request": false }

Create Follow-up Sequence

POST /api/sequences/create Body: { "api_key": "...", "profile_url": "...", "initial_message": "...", "num_followups": 3 }

Get Leads

GET /api/leads?api_key=...

Get Usage Stats

GET /api/usage?api_key=...

MCP Tools

When using as an MCP server, the following tools are available:

  • connect_browser: Connect to Chrome via CDP

  • setup_session: Authenticate LinkedIn session

  • search_leads: Search for LinkedIn leads

  • analyze_profile: Extract profile data

  • score_lead: AI-powered lead scoring

  • generate_message: Generate personalized messages

  • send_message: Send messages to profiles

  • create_followup_sequence: Create automated sequences

  • generate_api_key: Generate API keys

Tier Limits

Tier

Profiles

Messages

Sequences

Starter

500/month

200/month

2 active

Professional

2,000/month

1,000/month

10 active

Agency

10,000/month

5,000/month

Unlimited

Enterprise

Unlimited

Unlimited

Unlimited

Development

# Generate a test API key npm run generate-key # Run in development mode npm start

Production Deployment

  1. Set up PostgreSQL database (recommended: Neon)

  2. Configure environment variables

  3. Run database schema

  4. Deploy using PM2 or similar:

pm2 start src/http-server.js --name linkedin-mcp-api pm2 start src/worker.js --name linkedin-mcp-worker

Security Notes

  • ⚠️ Never commit - they contain sensitive credentials

  • 🔐 API keys are hashed using bcrypt

  • 🔒 All database queries use parameterized statements

  • 🛡️ CORS is configured for production use

License

MIT License - see LICENSE file for details

Author

Agentic AI AMRO Ltd

Support

For issues and feature requests, please open an issue on GitHub.

This server cannot be installed

-
security - not tested
F
license - not found
-
quality - not tested

How are these scores calculated?

Resources

New MCP Servers

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/vikram-agentic/linkedin-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server