Full-Stack Developer | MCP Specialist | Building AI-Powered Applications on Cloudflare Workers

I'm a software engineer specializing in Model Context Protocol (MCP) servers, RAG systems, and edge computing. I build production AI applications using Cloudflare Workers AI, Vectorize, and semantic search at global scale.

MCP Server Architecture on Cloudflare Workers

• Built 3 production MCP implementations (local stdio, hybrid, full edge HTTP)
• Published comprehensive guides on DEV.to (2K+ views)
• Sub-50ms semantic search globally using Workers AI + Vectorize
• Open-source implementations demonstrating MCP sampling patterns

FPL Hub - Fantasy Premier League Platform

• Serves 2,000+ users with 99.9% uptime
• Processes 500K+ daily API calls
• Real-time data pipeline with ML-powered predictions
• Built with React, Node.js, MongoDB, Cloudflare Workers

AI & Edge Computing:

• Model Context Protocol (MCP) server development
• RAG (Retrieval Augmented Generation) systems
• Semantic search with vector databases (Vectorize)
• Workers AI integration (embeddings, LLMs)
• Edge deployment & serverless architecture

Backend & Infrastructure:

• Cloudflare Workers, Pages, KV, R2, D1
• High-performance APIs (500K+ daily requests)
• Real-time data processing
• TypeScript, Node.js, Express.js

Frontend:

• React, Next.js, TypeScript
• Modern UI/UX with Tailwind CSS

AI/ML: Cloudflare Workers AI, Vectorize, RAG patterns, Semantic search, Embedding models

Cloud: Cloudflare Workers, Pages, KV, R2, D1, Serverless

Backend: Node.js, TypeScript, Express.js, RESTful APIs

Frontend: React, Next.js, TypeScript, Tailwind CSS

Database: MongoDB, PostgreSQL, SQLite, Vector databases

DevOps: Docker, CI/CD, Git, Performance optimization

Technical Articles on DEV.to:

• MCP Sampling on Cloudflare Workers - Making tools intelligent without managing LLMs
• Building MCP Servers on Cloudflare Workers - Edge deployment with semantic search
• AI-Powered FAQ System - Production RAG implementation

Combined views: 3K+ | Shared to 200K+ developers

HTTP-based MCP server deployed to Cloudflare's edge

• Semantic search with Workers AI + Vectorize
• Sampling context for intelligent tool responses
• Sub-50ms global latency
• Production-ready with CORS, error handling

Local MCP server bridging to Workers backend

• stdio transport for Claude Desktop
• True sampling implementation
• Hybrid architecture pattern

Fantasy Premier League analytics platform

• 2,000+ active users, 99.9% uptime
• 500K+ daily API calls
• ML-powered price predictions
• Real-time match tracking

AI-powered FAQ with RAG

• Workers AI + Vectorize integration
• Semantic search + answer generation
• Admin dashboard with React
• Production deployment patterns

Cobalt.tools - Contributed to media downloading tool (50K+ stars)

• International collaboration
• Large-scale codebase serving millions globally

• 💼 Upwork: Daniel Nwaneri
• 📝 DEV.to: @dannwaneri
• 📧 Email: [email protected]
• 🐦 Twitter: @dannwaneri
• 📍 Location: Port Harcourt, Nigeria

• MCP server development and architecture consulting
• Cloudflare Workers AI implementations
• RAG system design and deployment
• Semantic search and vector database integration
• Edge computing and serverless architecture
• Technical writing and developer advocacy

✅ Built production MCP servers deployed globally on Cloudflare's edge ✅ Published technical guides with 3K+ views, shared to 200K+ developers ✅ Engineered platform serving 2,000+ users with 99.9% uptime ✅ Processes 500K+ daily API calls with sub-second response times ✅ Achieved 60% page load reduction through optimization ✅ Open-source contributor to high-impact projects (50K+ stars)

"Every complex problem can be solved by breaking it down into fundamental subsets."

I focus on building scalable, production-ready solutions that combine clean architecture with cutting-edge AI capabilities. Whether it's deploying MCP servers at the edge, designing RAG systems, or optimizing high-traffic APIs, I prioritize both technical excellence and user experience.

⭐️ Open to work on exciting AI and edge computing projects!

Check out my pinned repos below for production MCP implementations and technical deep-dives.