HeadHunter MCP Server

Executive Technology Leadership Placement System - A comprehensive MCP server for researching companies, analyzing job opportunities, and preparing for executive technology roles.

Overview

HeadHunter MCP Server provides AI-powered tools for executive job hunting and career advancement in technology leadership roles. It offers comprehensive company research, LinkedIn intelligence, revenue engine analysis, and strategic interview preparation.

Key Features

• 🏢 Company Research: Deep analysis of business models, technology stacks, and strategic challenges
• 🔗 LinkedIn Intelligence: ToS-compliant relationship mapping and warm introduction pathfinding
• 💰 Revenue Engine Mapping: P&L impact analysis for technical decisions and platform investments
• 🎯 Interview Preparation: Architecture scenarios, business cases, and executive-level questions
• 📋 Executive Briefing: Comprehensive summaries and strategic preparation materials
• 📅 30-60-90 Day Planning: Strategic onboarding plans for executive roles

Installation

NPM Package

npm install -g @headhunter/mcp-server

Claude Desktop Configuration

Add to your Claude Desktop MCP configuration:

{
  "mcpServers": {
    "headhunter": {
      "command": "npx",
      "args": ["-y", "@headhunter/mcp-server"]
    }
  }
}

Development Setup

git clone https://github.com/your-org/headhunter-mcp-server
cd headhunter-mcp-server
npm install
npm run build
npm run dev

Available Tools

research_company

Research a company for executive technology roles with comprehensive business and technical analysis.

Parameters:

• company (required): Company name to research
• role (optional): Target role (default: "VP Engineering")
• focus_areas (optional): Specific areas to analyze

Example:

{
  "name": "research_company",
  "arguments": {
    "company": "Stripe",
    "role": "CTO",
    "focus_areas": ["revenue_engine", "tech_stack", "team_analysis"]
  }
}

analyze_revenue_engine

Map how company's technical systems drive revenue and costs for P&L impact analysis.

Parameters:

• company (required): Company name to analyze
• business_model (optional): Primary business model
• focus (optional): Analysis focus area

Example:

{
  "name": "analyze_revenue_engine",
  "arguments": {
    "company": "Notion",
    "business_model": "B2B SaaS",
    "focus": "growth_levers"
  }
}

linkedin_intelligence

Analyze LinkedIn relationships and find warm introduction paths (ToS-compliant).

Parameters:

• company (required): Target company name
• role (optional): Target role for team research
• export_data (optional): Path to LinkedIn export data
• research_depth (optional): Depth of research

Example:

{
  "name": "linkedin_intelligence",
  "arguments": {
    "company": "Figma",
    "role": "VP Engineering",
    "research_depth": "comprehensive"
  }
}

interview_preparation

Generate comprehensive interview preparation including scenarios and questions.

Parameters:

• company (required): Company name
• role (required): Target role
• interview_type (optional): Type of preparation
• focus_areas (optional): Specific preparation areas

Example:

{
  "name": "interview_preparation",
  "arguments": {
    "company": "Airbnb",
    "role": "Head of Platform",
    "interview_type": "comprehensive",
    "focus_areas": ["architecture", "leadership", "strategy"]
  }
}

executive_brief

Generate executive summary brief for target role application.

Parameters:

• company (required): Company name
• role (required): Target role
• application_stage (optional): Current stage
• include_sections (optional): Sections to include

Example:

{
  "name": "executive_brief",
  "arguments": {
    "company": "Datadog",
    "role": "VP Engineering",
    "application_stage": "interview"
  }
}

create_30_60_90_plan

Create detailed 30-60-90 day plan for executive technology role.

Parameters:

• company (required): Company name
• role (required): Target role
• team_size (optional): Expected team size
• key_challenges (optional): Known challenges
• focus_style (optional): Leadership style focus

Example:

{
  "name": "create_30_60_90_plan",
  "arguments": {
    "company": "Slack",
    "role": "CTO",
    "team_size": 120,
    "focus_style": "transformation"
  }
}

Usage Examples

Basic Company Research

// Research a company for VP Engineering role
const result = await client.callTool({
  name: "research_company",
  arguments: {
    company: "Stripe",
    role: "VP Engineering",
    focus_areas: ["technology", "business_model", "challenges"]
  }
});

Complete Application Preparation

// 1. Company research
const research = await client.callTool({
  name: "research_company",
  arguments: { company: "Notion", role: "CTO" }
});

// 2. Revenue engine analysis
const revenue = await client.callTool({
  name: "analyze_revenue_engine",
  arguments: { company: "Notion", focus: "comprehensive" }
});

// 3. LinkedIn intelligence
const linkedin = await client.callTool({
  name: "linkedin_intelligence",
  arguments: { company: "Notion", research_depth: "detailed" }
});

// 4. Interview preparation
const interview = await client.callTool({
  name: "interview_preparation",
  arguments: { company: "Notion", role: "CTO" }
});

// 5. Executive brief
const brief = await client.callTool({
  name: "executive_brief",
  arguments: { company: "Notion", role: "CTO" }
});

Privacy & Compliance

LinkedIn Terms of Service Compliance

• Export-First: Prioritizes LinkedIn data export over automated scraping
• Rate Limiting: Respects platform rate limits and usage guidelines
• User Consent: Only processes data with explicit user permission
• Public Data Only: When not using exports, only accesses publicly available information

Data Privacy

• Local Processing: All data processing happens locally by default
• No Data Storage: Does not store personal or professional data persistently
• Encryption: Sensitive data encrypted in transit and at rest
• GDPR Compliant: Respects user privacy rights and data protection regulations

Development

Project Structure

mcp-server/
├── src/
│   ├── index.ts          # Main MCP server implementation
│   ├── tools/            # Individual tool implementations
│   │   ├── company-research.ts
│   │   ├── linkedin-intelligence.ts
│   │   ├── revenue-engine.ts
│   │   ├── interview-prep.ts
│   │   └── executive-brief.ts
│   └── utils/            # Utility modules
│       ├── template-engine.ts
│       └── data-sources.ts
├── templates/            # Document templates
├── package.json
├── tsconfig.json
└── README.md

Building and Testing

# Install dependencies
npm install

# Build TypeScript
npm run build

# Run in development mode
npm run dev

# Run tests
npm test

# Lint code
npm run lint

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Configuration

Environment Variables

# Optional: API keys for enhanced data sources
CLEARBIT_API_KEY=your_clearbit_key
CRUNCHBASE_API_KEY=your_crunchbase_key
LINKEDIN_CLIENT_ID=your_linkedin_client_id
LINKEDIN_CLIENT_SECRET=your_linkedin_client_secret

# Optional: Custom data source URLs
COMPANY_DATA_API_URL=https://api.example.com
NEWS_API_KEY=your_news_api_key

Advanced Configuration

Create a .headhunterrc.json file in your project directory:

{
  "dataSources": {
    "enableWebScraping": true,
    "respectRobotsTxt": true,
    "rateLimitMs": 1000
  },
  "templates": {
    "customTemplatesPath": "./custom-templates"
  },
  "privacy": {
    "enableDataCaching": false,
    "encryptSensitiveData": true
  }
}

Use Cases

Executive Job Search

• Research target companies for strategic fit
• Map revenue impact of technical decisions
• Find warm introduction paths to hiring managers
• Prepare for technical and leadership interviews
• Create compelling 30-60-90 day plans

Career Development

• Analyze industry trends and company positioning
• Understand revenue models and business challenges
• Build professional network strategically
• Prepare for internal promotions and role transitions

Strategic Planning

• Competitive analysis for technology decisions
• Business case development for platform investments
• Team scaling and organizational design
• Cross-functional collaboration strategies

Support & Resources

Documentation

• API Reference
• Configuration Guide
• Privacy & Security
• Contributing Guidelines

Community

• GitHub Issues
• Discussions
• Discord Community

Professional Services

• Custom implementation and integration
• Executive coaching and career consulting
• Enterprise licensing and white-label solutions
• Training and workshops

License

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

Acknowledgments

• Built with Model Context Protocol (MCP)
• Inspired by executive technology leadership best practices
• Community contributions and feedback
• Privacy-first approach to professional data handling

HeadHunter MCP Server - Empowering executive technology leadership through AI-powered career intelligence.

For more information, visit https://headhunter-mcp.com or contact [email protected].