sales-mcp

AI-powered sales automation MCP for strategic guidance API business

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Sales MCP - Authority-as-a-Service Sales Automation

Intelligent sales automation MCP server for Cereve's Authority-as-a-Service category creation.

Features
  • 🔍 Intelligent Prospect Research - Automated company analysis and qualification
  • 📧 Authority-as-a-Service Email Generation - Tesla strategy cold emails with IP protection
  • 📊 Lead Scoring & Qualification - Smart prioritization of prospects
  • 🚀 Gmail Integration - Automated sending and tracking
  • 📈 Category Creation Pipeline - Complete Authority-as-a-Service outreach workflow
Quick Start
# Install dependencies
npm install

# Set up environment
cp env.example .env
# Edit .env with your API keys

# Start development server
npm run dev
Setup
1. Environment Configuration

Copy the example environment file and configure your API keys:

cp env.example .env

Required environment variables:

  • OPENAI_API_KEY - Your OpenAI API key for email generation
  • GOOGLE_CLIENT_EMAIL - Gmail service account email
  • GOOGLE_PRIVATE_KEY - Gmail service account private key
2. Gmail API Setup

For detailed Gmail OAuth2 setup instructions, see GMAIL_SETUP.md.

Quick setup:

  1. Go to Google Cloud Console
  2. Create a new project or select existing one
  3. Enable Gmail API
  4. Create OAuth2 credentials (Desktop application)
  5. Run the setup script: npm run setup-gmail
  6. Follow the prompts to authorize and get refresh token
Available Tools
1. research_prospect

Research and qualify a prospect company for sales outreach.

Parameters:

  • company_name (string) - Name of the company to research

Returns: Comprehensive company data including:

  • Platform type classification
  • Revenue and employee information
  • Funding status
  • Qualification score and tier
  • Technical stack analysis
2. generate_email

Generate an Authority-as-a-Service cold email using Tesla strategy (protect IP before NDA).

Parameters:

  • company_name (string) - Name of the prospect company
  • recipient_name (string) - Name of the recipient
  • recipient_title (string) - Job title of the recipient

Returns: Authority-as-a-Service cold email with subject, body, and personalization score

3. generate_email_from_research

Generate an Authority-as-a-Service cold email using existing research data.

Parameters:

  • research_data (object) - Complete research data from research_prospect tool
  • recipient_name (string) - Name of the recipient
  • recipient_title (string) - Job title of the recipient

Returns: Authority-as-a-Service cold email with subject, body, and personalization score

4. send_email

Send a sales email via Gmail API.

Parameters:

  • to (string) - Recipient email address
  • subject (string) - Email subject line
  • body (string) - Email body content
  • from_name (string, optional) - Sender name

Returns: Gmail message ID confirmation

5. qualify_prospect

Score and qualify a prospect based on research data.

Parameters:

  • company_data (object) - Company research data to qualify

Returns: Qualification score, tier, and breakdown

6. batch_research

Research multiple companies in batch.

Parameters:

  • company_names (array) - Array of company names to research

Returns: Array of research results for all companies

Authority-as-a-Service Target Platforms

The MCP is optimized for platforms where user abandonment occurs due to strategic uncertainty:

  • No-Code/Low-Code (Bubble, Webflow, Retool) - Users abandon projects due to business logic decisions
  • CRM (HubSpot, Pipedrive, Salesforce) - Sales teams abandon deals due to strategic uncertainty
  • Project Management (Asana, Monday.com, ClickUp) - Teams abandon projects due to planning gaps
  • E-commerce (Shopify, WooCommerce, BigCommerce) - Merchants abandon strategies due to market uncertainty
  • Automation (Zapier, Make.com, Integromat) - Users abandon automation due to strategic complexity
Qualification Scoring

Prospects are scored on multiple criteria:

  • Platform Type (30 points max)
  • Company Size (25 points max)
  • Growth Indicators (20 points max)
  • Technical Fit (15 points max)
  • Contact Quality (10 points max)
Qualification Tiers
  • Hot (80+ points) - Immediate outreach
  • Warm (60-79 points) - Research more
  • Cold (40-59 points) - Nurture campaign
  • Not Qualified (<40 points) - Skip
Usage Examples
Research a Prospect
// Research a no-code platform company
const result = await research_prospect({
  company_name: "Bubble"
});
Generate Authority-as-a-Service Cold Email
// Generate Authority-as-a-Service cold email for Monday.com's CEO
const email = await generate_email({
  company_name: "Monday.com",
  recipient_name: "Roy Mann",
  recipient_title: "CEO"
});

// Or use existing research data
const research = await research_prospect({ company_name: "Monday.com" });
const email = await generate_email_from_research({
  research_data: research,
  recipient_name: "Roy Mann",
  recipient_title: "CEO"
});
Send Authority-as-a-Service Email
// Send the Authority-as-a-Service cold email
await send_email({
  to: "roy@monday.com",
  subject: email.subject,
  body: email.body,
  from_name: "Cereve Team"
});
Logging

The MCP includes comprehensive logging:

  • Console output - Real-time development feedback
  • File logs - Persistent logging in logs/ directory
  • Error tracking - Separate error log file
  • Performance monitoring - Operation timing and metrics

Log levels can be configured via LOG_LEVEL environment variable.

Development
# Start development server with auto-reload
npm run dev

# Start production server
npm start

# Setup Gmail OAuth2 authentication
npm run setup-gmail

# Test Gmail integration
npm run test-gmail

# Test email generation
npm run test-email
Architecture
  • MCP Server - Core server implementation using Model Context Protocol
  • Research Engine - Multi-source company research and analysis
  • AI Email Generator - OpenAI-powered personalized email creation
  • Gmail Integration - Automated email sending via Gmail API
  • Qualification Engine - Intelligent prospect scoring and tiering
  • Caching System - Performance optimization with 24-hour cache TTL
Contributing
  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request
License

ISC License

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