RAG and MCP aren’t rivals—they’re complementary. RAG helps AI know by retrieving knowledge; MCP helps it act by executing tasks through standardized tool access. The future isn’t choosing one, but combining both to build AI agents that understand and get things done. Stop comparing—start architecting for action.
To move beyond isolated AI, a new set of communication standards is emerging to create a collaborative “Internet of Agents.” This guide explains the key protocols—MCP for tool access, A2A for internet-scale teamwork, and ACP for internal agent clusters—and how they form the foundational stack for the next generation of intelligent systems. By understanding how these protocols work together, technical leaders can design robust, interconnected AI architectures for the future.
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In today’s rapidly evolving technological landscape, the role of a data professional is undergoing a profound transformation. As businesses increasingly leverage AI and intelligent systems,… Read More »From Data Engineer to Data Lead: Guiding the Future of Intelligent Data
Machine learning (ML) is a branch of artificial intelligence (AI) that enables systems to learn patterns from data and make predictions or decisions without being… Read More »Core Machine Learning Concepts Explained