Author (Y): Harshit Kandoi
Originally published in the direction of artificial intelligence.
Imagine a network of AI systems consisting of virtual assistants, recommendations engines and robotic agents who work independently. But not “synchronized”. Every time you interact with one, you have to start from scratch, unaware of previous choices, the last interaction and even the idea he works on. Result? Unnecessary processes, uncomfortable experiences and there was no chance to enjoy the real automation of machines. This is a price that we have to pay for the loss of context and it has become a burning challenge in today's world based on AI.
Let's introduce the world Model Context Protocol (MCP), an innovative way that promises restructuring the method of interaction and cooperation of AI systems. MCP is a normalized framework created to enable the provision of contextual data between models, ensuring continuity, consistency and connectivity in these complex AI ecosystems.
Why does it matter now compared to always? As we know, artificial intelligence becomes more embedded in everything, from health services to autonomous systems, the need for intelligent division of context is not only technical convenience, but is a basic requirement. Without it, even the most powerful AI models operate in silos, unable to use collective knowledge or maintain user continuity.
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Published via AI
