Everyone is talking about Model Context Protocol (MCP) right now. But is it actually a fundamental shift in how we build AI infrastructure, or just marketing hype?
At its core, MCP solves a messy problem: bridging the gap between local data sources and remote LLMs without exposing sensitive data. It’s great for security and modularity, but it definitely introduces latency and architectural complexity.
Are you implementing MCP in your projects right now, or are you sticking to standard API integrations for now? Let's discuss the reality versus the hype below.
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