Most MCP tutorials teach you tools and stop there. The protocol gives you three primitives, and they are three different cost and trust boundaries — which is where your latency, your permission surface and your duplicated prompts actually live.

Five bugs from one hackathon build. Every one of them failed silently, and every one failed silently for the same reason: the subsystem was designed to degrade instead of crash.

My personal reference for working with Claude Code — context management + the full build workflow. Written to skim, not to read cover to cover.

Notes on understanding and building with the Model Context Protocol (MCP) using Go. Rather than being a complete guide, this is a breakdown of the concepts, mental models, architecture decisions, and implementation details that helped me understand how MCP enables AI agents to interact with tools, resources, and external systems in a structured way. I also explore why I chose Go over the more common Python/TypeScript stack, how MCP transports work, and why I believe MCP has the potential to become a foundational capability layer for intelligent systems. If you are a backend engineer curious about AI infrastructure, agent systems, orchestration, or protocol design, this article is for you.

Discover how to build secure, context-aware AI systems. In this deep dive, I share my journey architecting the Lineage MCP server for blockchain execution and orchestrating multi-agent workflows with Google ADK to build MergeOracle—tackling precision errors, observability, and agent hallucinations along the way.

In this technical deep dive, I move past surface-level definitions to explore the theoretical foundations of distributed consensus. Written during a midnight study session in Lagos, this article serves as a comprehensive guide for aspiring protocol engineers.

A Living Archive of Concepts & Implementations I Am Encountering Transitioning To Protocol Engineering