The Sequence Opinion #542 : Some Ideas About the Future of MCP
Better discovery, networking models, memory and others.
I’ve been spending a lot of time on Model Context Protocol (MCP) in the last few weeks and wanted to share some ideas.
MCP has quickly become a cornerstone in enabling AI models—particularly large language models (LLMs) and autonomous agents—to interact with external tools, APIs, and data sources through a standardized interface. Much like USB-C revolutionized device connectivity, MCP aims to standardize how models access and apply contextual information.
While MCP initially focused on simplifying integrations, its broader impact is now coming into view. We're beginning to see MCP evolve into a foundational layer for distributed AI systems. These systems involve not just a single model with a static toolbox, but networks of interoperating agents, dynamically discovering, invoking, and coordinating with external resources.
This article explores where MCP is headed in the next 3–5 years. We look at five key areas: federated discovery, decentralized MCP networks, persistent and transferable context, trust and cryptographic guarantees, and AI-native protocol interactions such as context negotiation and orchestration. These directions mark a shift from tool access to context-rich, agentic ecosystems.