<ul><li>Shrijith Venkatrama, founder of Hexmos, is exploring the Model Context Protocol (MCP) for AI apps' context and tools.</li><li>MCP aims to connect AI to various elements like data, user inputs, and workflows using JSON-RPC.</li><li>The architecture involves Hosts, Clients, and Servers working together to enhance AI capabilities.</li><li>Hosts manage the AI app, while Clients serve as connectors to Servers that provide context and tools.</li><li>Servers deliver callable functions, prompts (workflows), and resources to AI applications.</li><li>Clients maintain stateful sessions and pass messages between Hosts and Servers in the MCP setup.</li><li>MCP's stateful design and terminology like 'sampling' pose challenges for clear interpretation and implementation.</li><li>The potential of MCP lies in enhancing AI context, guiding user flows, and enabling modular server interactions.</li><li>Implementing MCP could benefit chatbot development, content generation, and real-time data integration for AI models.</li><li>Starting with a basic setup and experimenting with JSON-RPC interactions can help developers explore the capabilities of MCP.</li></ul>

My Notes on Model Context Protocol Architecture: A Developer’s Dive

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