Architecting with Claude Code: From MCP Servers to Production Efficiency

Modern AI development is increasingly moving toward tool-driven, context-aware workflows , where models integrate deeply with development environments. Tools like Claude Code enable developers to build efficient, structured, and scalable AI-assisted systems directly from the command line.

In this session, we will explore the architecture of Claude Code and how to leverage it effectively for real-world development. You’ll learn how to use Claude.md for project memory and context management, set up Model Context Protocol (MCP) servers, and design custom skills to extend functionality.

We will also cover best practices for token efficiency and architectural design , helping you build lean, high-performance AI workflows.

This is a practical and architecture-focused session designed to help you get the most out of Claude Code in production environments.

Key Takeaways:

• Claude Code Fundamentals – understanding its role in AI-driven development
• Context Management – using Claude.md for memory and workflow structuring
• MCP Integration – setting up and leveraging MCP servers
• Custom Skills – extending capabilities for specific use cases
• Efficiency & Design – optimizing token usage and system architecture

Prerequisites:

• Basic understanding of Claude Code
• (Optional) Claude Code installed and running in your terminal

Nitish is an AI Analyst based in London, working within the startup ecosystem. He is passionate about building and shipping innovative AI-driven products and enjoys exploring new ideas in AI architecture.