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Gmail MCP Agent

MCP Server

一个企业级的潜在客户培育系统,通过Gmail自动化外联活动,包括智能跟进、响应跟踪和24/7运行。

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PythonGmail集成团队协作

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

作者 / 组织

brandononchain

提供方

brandononchain

最后核验

2026/5/17 20:23

快速接入

先看主来源和安装命令,再打开仓库或文档;下面只保留这个条目的关键接入事实。

命令预览

pip install -r requirements.txt

详细介绍

🤖 Gmail MCP Agent - 24/7 Lead Nurturing System

A comprehensive, enterprise-grade lead nurturing system that automates Gmail outreach campaigns with intelligent follow-ups, response tracking, and 24/7 operation via MCP (Model Context Protocol) server.

🚀 Features

Automated Lead Nurturing

  • 24/7 Operation - Runs continuously with Docker containerization
  • Intelligent Follow-ups - Automatic sequences at 3 days and 7 days
  • Response Tracking - Monitors Gmail for replies and categorizes them
  • Lead Scoring - Tracks engagement and interest levels
  • Smart Responses - Automatically responds to interested leads

📊 MCP Server Architecture

  • Remote Control - Control system via MCP protocol
  • Real-time Monitoring - Live status and performance tracking
  • Docker Deployment - Production-ready containerization
  • Health Checks - Automatic recovery and error handling
  • Scalable Design - Ready for enterprise use

🎯 Email Campaign Management

  • CSV-based Lead Lists - Easy contact management
  • Template System - Jinja2-powered email personalization
  • Rate Limiting - Respects Gmail API quotas
  • Resume Capability - Continue from where you left off
  • Comprehensive Logging - Complete audit trail

📁 Project Structure

├── send_from_csv.py          # Main Gmail sender script
├── lead_nurturer.py          # Automated nurturing system
├── mcp_server.py             # 24/7 MCP server
├── mcp_client.py             # Control interface
├── lead_dashboard.py         # Monitoring dashboard
├── run_nurturing.py          # Automation runner
├── contacts.csv              # Lead database (96 dental practices)
├── body.txt                  # Email template
├── credentials.json          # Gmail API credentials
├── nurturing_config.json     # System configuration
├── gmail_sync_state.json     # Gmail incremental sync state (auto-created)
├── requirements.txt          # Python dependencies
├── Dockerfile               # Container configuration
├── docker-compose.yml       # Deployment setup
├── deploy.sh                # One-click deployment
└── DEPLOYMENT_GUIDE.md      # Complete setup guide

🛠️ Quick Start

1. Clone and Setup

git clone https://github.com/brandononchain/GMAIL-MCP-Agent.git
cd GMAIL-MCP-Agent
pip install -r requirements.txt

2. Configure Gmail API

  • Get OAuth2 credentials from Google Cloud Console
  • Save as credentials.json
  • Update sender email in nurturing_config.json

3. Deploy 24/7 System

# Docker deployment (recommended)
./deploy.sh

# Or manual deployment
docker-compose up -d

4. Start Nurturing

# Using MCP client
python mcp_client.py start 4

# Or direct execution
python run_nurturing.py

🎮 Control Commands

MCP Client Interface

# Start nurturing system (every 4 hours)
python mcp_client.py start 4

# Check system status
python mcp_client.py status

# Get lead report
python mcp_client.py report

# Send test email
python mcp_client.py test your-email@example.com

# View recent logs
python mcp_client.py logs 100

# Stop the system
python mcp_client.py stop

Direct Scripts

# Run single nurturing cycle
python lead_nurturer.py

# View lead dashboard
python lead_dashboard.py

# Send emails from CSV
python send_from_csv.py contacts.csv --body_file body.txt

📊 Current Campaign

Dental Practice Outreach

  • Target: 96 dental practices in Chicago
  • Message: AI lead follow-up system for dental practices
  • Follow-up Schedule: 3 days and 7 days after initial contact
  • Expected Results: 20-30% response rate, 10-15% conversion

Email Template

Hi {{first_name}},

Did you know many dental practices lose 20–30% of new patient inquiries because follow-ups slip through the cracks?

We've built an AI agent that automatically follows up with every lead via SMS/email and books them straight into your calendar.

Clients typically see 5–9 extra appointments in the first 30 days.

Have time for 10-min demo call this week?

Thank you,
Brandon
Quantra Labs

🔧 Configuration

Environment Variables

# Gmail API Configuration
CREDENTIALS_FILE=credentials.json
TOKEN_FILE=token.json

# Nurturing Settings
PER_MINUTE=12
RESUME=false
LOG_FILE=send_log.csv

# MCP Server Settings
MCP_SERVER_PORT=8000
LOG_LEVEL=INFO

Nurturing Configuration

{
  "sender_email": "your-email@domain.com",
  "follow_up_schedule": {
    "followup_1_days": 3,
    "followup_2_days": 7
  },
  "automation": {
    "check_responses_interval_hours": 4,
    "auto_respond_to_interest": true
  }
}

📈 Performance Metrics

Expected Results

  • Response Rate: 20-30% from initial outreach
  • Follow-up Response: 40-60% from follow-ups
  • Conversion Rate: 10-15% to interested leads
  • Automation Coverage: 80% of responses handled automatically
  • Uptime: 99.9% with Docker restart policies

Monitoring

  • Real-time lead scoring and status tracking
  • Response rate analytics and conversion metrics
  • System health monitoring and error reporting
  • Complete audit trail of all interactions

🚀 Deployment Options

Docker (Recommended)

# One-click deployment
./deploy.sh

# Manual deployment
docker-compose up -d

Local Development

# Install dependencies
pip install -r requirements.txt

# Run nurturing system
python run_nurturing.py

Production Server

# Systemd service
sudo cp lead-nurturing.service /etc/systemd/system/
sudo systemctl enable lead-nurturing
sudo systemctl start lead-nurturing

🔒 Security & Privacy

  • Local Data Storage - All data remains on your server
  • OAuth2 Authentication - Secure Gmail API access
  • No External Services - No data sent to third parties
  • Encrypted Credentials - Secure credential management
  • Audit Logging - Complete activity tracking

📞 Support & Documentation

  • Deployment Guide: DEPLOYMENT_GUIDE.md
  • Nurturing Guide: NURTURING_README.md
  • Debug Report: DEBUG_REPORT.md
  • Docker Setup: docker-compose.yml

🎯 Use Cases

Sales Outreach

  • B2B lead generation and nurturing
  • Automated follow-up sequences
  • Response tracking and lead scoring

Marketing Campaigns

  • Email marketing automation
  • A/B testing and optimization
  • Performance analytics

Customer Success

  • Onboarding email sequences
  • Renewal and upsell campaigns
  • Customer feedback collection

📊 System Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────┐
│   MCP Client    │◄──►│   MCP Server     │◄──►│  Lead Nurturer  │
│  (Control)      │    │  (24/7 Service)  │    │  (Automation)   │
└─────────────────┘    └──────────────────┘    └─────────────────┘
                                │
                                ▼
                       ┌──────────────────┐
                       │   Gmail API      │
                       │  (Email System)  │
                       └──────────────────┘

🏆 Enterprise Features

  • 24/7 Operation - Continuous automation
  • Scalable Architecture - Handle thousands of leads
  • Professional Monitoring - Real-time dashboards
  • Error Recovery - Automatic failure handling
  • Audit Compliance - Complete activity logging
  • Docker Deployment - Production-ready containerization

Ready to automate your lead nurturing? 🚀

This system is production-ready and can handle enterprise-scale email campaigns with full automation, monitoring, and 24/7 operation.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

📧 Contact

目录标签

目录标签

PythonGmail集成团队协作邮件营销本地部署自动化潜在客户管理企业级

接入字段

传输方式(transport,传输协议)

stdio

鉴权方式(authType,认证方式)

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来源信息

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