MODEL CONTEXT PROTOCOL
BY TONY LAMA, AVAYA
ILLUSTRATION PROVIDED BY ADOBE STOCK
WHAT CONTACT CENTERS SHOULD KNOW ABOUT MCP HOW MCP HELPS AI SYSTEMS ACCESS
AI has quickly become an integral component of modern contact centers, playing a central role in interpreting customer intent and guiding real-time decisions.
Virtual agents and agent-assist tools, along with analytics, quality management, and workforce optimization, now rely heavily on AI to support both customers and agents.
As organizations deploy more AI-driven capabilities, they face a foundational challenge: providing AI systems with accurate and secure context across environments that continue to become more complex.
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CONTEXT MORE RELIABLY.
For without the right context, even advanced AI models can produce unreliable outputs or responses that fail to align with business rules or regulatory requirements.
This challenge has driven growing interest in an emerging concept known as the Model Context Protocol( MCP). MCP is not a product or a single technology, but an approach to standardizing how AI models access and use contextual information from enterprise systems.
While adoption is still in the early stages, MCP has important implications for how contact centers scale AI in a responsible and effective way.
WHY CONTEXT IS A GROWING CHALLENGE
Context has always been fundamental to effective customer service. Human agents rely on customers’ histories, previous interactions, policies, and real-time signals to resolve issues efficiently and accurately.
But as AI takes on a greater role in customer interactions, those same requirements apply but at a far greater speed and scale.