MCP-Powered Lead Gen + Enrichment + Outreach System

A full-stack lead generation and outreach automation system built with Model Context Protocol (MCP), n8n orchestration, Groq AI, and a real-time monitoring dashboard.

🎯 Features

• Lead Generation: Generate 200+ realistic leads with valid contact information
• AI Enrichment: Enrich leads with company insights, personas, and pain points using Groq LLM
• Message Personalization: Create personalized emails and LinkedIn DMs with A/B variations
• Smart Outreach: Send messages with retry logic, rate limiting, and error handling
• Real-time Monitoring: Track pipeline progress with a modern React dashboard
• MCP Integration: Orchestrate workflow through Model Context Protocol
• n8n Workflow: Visual workflow automation and orchestration

🏗️ Architecture

┌─────────────┐      ┌──────────────┐      ┌─────────────┐
│   n8n       │─────▶│  MCP Server  │─────▶│   Backend   │
│  Workflow   │      │   (Tools)    │      │  Services   │
└─────────────┘      └──────────────┘      └─────────────┘
                            │                      │
                            │                      ▼
                            │               ┌─────────────┐
                            │               │   SQLite    │
                            │               │   Database  │
                            │               └─────────────┘
                            ▼
                     ┌──────────────┐
                     │   Frontend   │
                     │  Dashboard   │
                     └──────────────┘

📋 Prerequisites

• Python 3.10+
• Node.js 18+
• n8n (remote self-hosted instance)
• Groq API key (free tier available at https://console.groq.com)
• ngrok account (free tier available at https://ngrok.com)

🚀 Quick Start

1. Clone and Setup

cd e:\intern-assigment\linkind-mcp

2. Configure Environment

# Copy example environment file
cp .env.example .env

# Edit .env and add your Groq API key
# GROQ_API_KEY=your_key_here

3. Install Python Dependencies

# Create virtual environment
python -m venv venv

# Activate virtual environment
# Windows:
venv\Scripts\activate
# Linux/Mac:
source venv/bin/activate

# Install dependencies
pip install -r requirements.txt

4. Install Frontend Dependencies

npm install

5. Initialize Database

python backend/database.py

6. Start the Services

Terminal 1 - MCP Server:

python mcp_server/server.py

Terminal 2 - API Backend:

python backend/api.py

Terminal 3 - Frontend:

npm run dev

7. Access the Applications

• Frontend Dashboard: http://localhost:3000
• API Backend: http://localhost:8000
• API Docs: http://localhost:8000/docs
• n8n Editor: Your remote n8n instance URL

8. Setup ngrok Tunnel

To connect your local API with the remote n8n instance:

# In a new terminal, start ngrok
ngrok http 8000

Copy the ngrok URL (e.g., https://abc123.ngrok-free.app) and update your n8n workflow nodes to use this URL.

📁 Project Structure

linkind-mcp/
├── backend/              # Python backend services
│   ├── api.py           # FastAPI application
│   ├── database.py      # SQLite database setup
│   ├── lead_generator.py # Lead generation logic
│   ├── enrichment.py    # Lead enrichment service
│   ├── messaging.py     # Message generation
│   └── outreach.py      # Message sending
├── mcp_server/          # MCP server implementation
│   ├── server.py        # MCP server main
│   └── tools.py         # MCP tool definitions
├── frontend/            # Next.js React frontend
│   ├── pages/          # Next.js pages
│   ├── components/     # React components
│   └── styles/         # CSS styles
├── data/               # SQLite database storage
├── .env.example        # Environment template
└── README.md           # This file

🔧 Configuration

Dry Run vs Live Run

Toggle between modes in the frontend or set in .env:

DRY_RUN_MODE=true   # Logs messages without sending
DRY_RUN_MODE=false  # Actually sends messages

Rate Limiting

Configure in .env:

RATE_LIMIT_PER_MINUTE=10  # Max messages per minute
MAX_RETRIES=2             # Retry attempts for failed sends

Email Configuration

For live email sending, configure SMTP:

SMTP_HOST=smtp.gmail.com
SMTP_PORT=587
[email protected]
SMTP_PASSWORD=your_app_password  # Use Gmail App Password

🎮 Usage

How the System Works

The system now operates through automated triggers from external sources:

1. Lead Capture:

• Google Sheets: Add a new row with lead information
• Facebook Lead Ads: User submits an instant form

1. Automatic Processing:

• n8n detects the new lead from trigger
• Processes and normalizes the lead data
• Sends to your local API via ngrok
• API enriches the lead with AI insights
• Generates personalized messages
• Sends outreach (email/LinkedIn)

1. Monitor Progress:

• Open frontend dashboard at http://localhost:3000
• View real-time metrics and lead status
• Check enrichment data and generated messages

Pipeline Stages

1. Process Lead → Receives and validates external lead data
2. Enrich Lead → Adds AI-generated company insights and personas
3. Generate Messages → Creates personalized email + LinkedIn DM
4. Send Outreach → Delivers messages (or logs in dry-run mode)

Testing with Sample Data

Add a test lead to your Google Sheet with:

• Name: John Smith
• Email: [email protected]
• Phone: +1-555-0123
• Job Title: VP of Sales
• Company: TechCorp Solutions
• Comments: Interested in improving team productivity and automation tools

The n8n workflow will automatically detect and process it, generating personalized messages based on the comments provided.

n8n Workflow Setup

1. Access your n8n instance (remote self-hosted)
2. Import the workflow: Navigate to n8n and import n8n/n8n-workflow.json
3. Configure triggers:

• Google Sheets Trigger: Connect your Google account and select the spreadsheet with lead data
• Required columns: name, email, phone, job_title, company, comments
• Facebook Lead Ads Trigger: Connect your Facebook account and select the form
• Required fields: full_name, email, phone_number, job_title, company_name, comments

1. Update API endpoints: Replace placeholder URLs in all HTTP Request nodes with your ngrok URL:

• Run Pipeline: https://YOUR-NGROK-URL.ngrok-free.app/pipeline/run
• Get Metrics: https://YOUR-NGROK-URL.ngrok-free.app/metrics
• Get Leads: https://YOUR-NGROK-URL.ngrok-free.app/leads

1. Activate the workflow

🧪 Testing

Test Lead Processing

python backend/lead_generator.py

Test API Endpoint

curl -X POST http://localhost:8000/pipeline/run \
  -H "Content-Type: application/json" \
  -d '{
    "dry_run": true,
    "enrichment_mode": "offline",
    "lead_count": 200,
    "channel": "both",
    "lead_data": {
      "name": "Jane Doe",
      "email": "[email protected]",
      "phone": "+1-555-0199",
      "job_title": "CTO",
      "company": "Innovation Labs",
      "comments": "Looking for AI solutions to streamline operations",
      "source": "test"
    }
  }'

📊 Database Schema

Leads are tracked through these statuses:

• NEW → Lead created
• ENRICHED → Lead enriched with insights
• MESSAGED → Messages generated
• SENT → Outreach sent successfully
• FAILED → Process failed

🆓 Free Resources Used

• Groq: Free tier LLM API (100 requests/minute)
• SQLite: Local database (no limits)
• n8n: Self-hosted open-source (free)
• ngrok: Free tier for tunneling (https://ngrok.com)
• External Lead Sources: Facebook Lead Ads, Google Sheets
• FastAPI: Python web framework
• Next.js: React framework

<<<<<<< HEAD

🔐 Security Notes

• Keep your ngrok URL private - it exposes your local API
• Rotate ngrok URLs regularly (free tier URLs change on restart)
• Use environment variables for sensitive data
• Enable authentication on n8n in production
• Never commit .env files to version control

📝 License

MIT

🤝 Contributing

This is a take-home assignment project. For production use, consider adding:

• Unit tests
• WebSocket/SSE for real-time updates
• Multi-tenant support
• Export functionality
• Advanced targeting rules
• Mailhog (optional): Local SMTP testing server