lyr3

Lyr3.com is happy to present its MPC Registry as a beta.

MCP continues to expand its reach across enterprise and developer ecosystems, with new use cases, platform adoption, and benchmarks revealing both promise and challenges.

Chat boxes have become the face of AI. We type, the AI replies, and when tools are connected through MCP (Model Context Protocol), the outputs are poured back into text. Clean, minimal plumbing.

But MCP-Universe, a benchmarking project, shows just how brittle that model is. Only about one-third of complex interactions succeed when the AI has to juggle multi-step orchestration entirely through chat. That raises a question: are we overloading the AI, and forcing the chat box to do too much?

When people hear “Model Context Protocol (MCP),” it sounds abstract and technical—like plumbing for AI systems. But if you strip it down, MCPs are really just goal-oriented choose-your-own-adventure games written for AI.

On LinkedIn I wrote a short piece on how the limitations of AI impact the design and architecture of AIUX, the process of designing interfaces for AI. We will need to pay close attention to how this develops.

MDN (Markdown Notation) project defining a simple, AI-readable spec for representing tabular and contextual data for AI systems

An application that uses AI to provide critical feedback in go-to-market decisions.

Outcome: Startup concept, effective technology but could not resolve on GTM. Retired.

The real opportunity in the AI era isn't building AI tools, but creating AI-native companies that fundamentally rethink how value gets created and delivered.

Exploring how compliance, audit, and defensibility change when AI becomes part of the workflow.

Outcome: Developed AI tool to write compliance training scripts and documents.

Client Project

How combining multiple AI proofreaders with consensus-based decision making can achieve better results than either humans or AI alone.

Client Project