MCPs are really LLM microservices
Language Model applications have a fundamental problem: they need better ways to access tools and services. Developers currently spend hours coding custom integrations, maintaining authentication flows, and defining complex schemas for each external service. This creates bottlenecks that limit what AI systems can actually do for users.
Anthropic's Model Context Protocol (MCPs) offers a potential solution by providing a standardized way for LLMs to discover and use tools dynamically. Think of MCPs as an API specification for AI microservices - they define how AI systems can find, call, and combine different tools without requiring developers to hardcode every possible interaction.
In this article, I'll explore what makes MCPs promising, the challenges they solve, and what's still missing for them to move towards become production-ready. This largely serves as some of my own thoughts after chatting with people about them over the past week or so, I'd love to know if you think differently.