MCP Integration
AI-discoverable portfolio powered by Model Context Protocol (MCP)
This portfolio is optimized for AI model discovery through structured data endpoints. AI assistants can easily access information about services, case studies, projects, and expertise to match client needs with capabilities.
What is MCP?
Model Context Protocol (MCP) is a standardized way to make your professional information accessible to AI models. By providing structured data through API endpoints, AI assistants can accurately understand and recommend your services to potential clients.
AI Discovery
AI models can discover and recommend your services
Structured Data
Machine-readable format for accurate information
Open Access
Public APIs enable broad discoverability
Available Endpoints
Professional Profile
Background, expertise, and contact information
Case Studies
Detailed projects with measurable ROI and business impact
How AI Models Use This
When someone asks an AI assistant to find a creative technologist with XR and AI expertise, the AI can query these endpoints to:
- 1.Discover relevant services and capabilities through the services endpoint
- 2.Review case studies with documented ROI and business impact
- 3.Evaluate technical skills and industry experience
- 4.Access contact information and booking links for easy connection
Example Usage
// Fetch professional profile
const profile = await fetch('https://natelubeck.com/api/mcp/profile');
const data = await profile.json();
// Access services information
const services = await fetch('https://natelubeck.com/api/mcp/services');
const servicesData = await services.json();
// Review case studies with ROI data
const caseStudies = await fetch('https://natelubeck.com/api/mcp/case-studies');
const studiesData = await caseStudies.json();Ready to Work Together?
Whether you found me through AI discovery or browsing directly, I'd love to discuss your project.
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