Apr 24
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Google just made a move that could change how AI agents work in production. Until now, MCP (Model Context Protocol) solved the integration chaos between AI agents and tools. But Enterprises already run on gRPC. MCP was built on JSON over HTTP. That mismatch created real problems: • Duplicate protocol stacks • Performance overhead • Lack of type safety Now Google is introducing a gRPC transport layer for MCP. In this video, we break down: • How MCP actually works (in simple terms) • Why the transport layer matters more than you think • The real problems enterprises faced with MCP • How gRPC fixes those limitations • Whether this actually improves performance or not • What this means for the future of AI agents If you’re building AI agents, working with microservices, or running gRPC in production, this is something you need to understand. 📚 Related Resources: → ByteMonk Blog: https://blog.bytemonk.io/ → System Design Course: https://academy.bytemonk.io/courses → LinkedIn: https://www.linkedin.com/in/bytemonk/ → Github: https://github.com/bytemonk-academy → GRPC: https://youtu.be/4w8pEyJMpvo?si=GgG26QnYVMaTrwaX → MCP: https://youtu.be/MI796yMnOF0?si=4QcdIjlKM2mQQkEt Timestamps: 00:00 Google announcement 00:33 What MCP Actually Solves 02:10 The Hidden Problem (Transport Layer) 04:00 Why Enterprises Struggle with MCP 06:21 Google’s gRPC Solution 08:00 Is This Actually Worth It? 09:10 What This Means Going Forward https://www.youtube.com/playlist?list=PLJq-63ZRPdBt423WbyAD1YZO0Ljo1pzvY https://www.youtube.com/playlist?list=PLJq-63ZRPdBssWTtcUlbngD_O5HaxXu6k https://www.youtube.com/playlist?list=PLJq-63ZRPdBu38EjXRXzyPat3sYMHbIWU https://www.youtube.com/playlist?list=PLJq-63ZRPdBuo5zjv9bPNLIks4tfd0Pui https://www.youtube.com/playlist?list=PLJq-63ZRPdBsPWE24vdpmgeRFMRQyjvvj https://www.youtube.com/playlist?list=PLJq-63ZRPdBslxJd-ZT12BNBDqGZgFo58 #mcp #grpc #bytemonk