
How to build a world-class AI customer service team
Templates and guidance on building a customer service team that uses both AI and human agents to their fullest potential.
Learn MoreGenerative AI is transforming customer service faster than any other part of the business. But as AI agents take on more complex tasks, one big challenge remains: how to give them the right organizational context—safely, in real time, at scale.
Enter Model Context Protocol (MCP), an emerging standard with the potential to do for AI agents what USB-C did for devices: simplify connections, unlock interoperability, and accelerate innovation.
With 85% of CX leaders planning to adopt AI this year, MCP could be the missing link that helps AI agents go from helpful to extraordinary. Here’s what you need to know.
At the core of every AI agent lies a large language model (LLM). While these models have been trained on vast amounts of publicly available data from across the Internet, they have no inherent knowledge of an organization’s proprietary information, including internal data, policies, knowledge bases, and compliance frameworks.
This is by design. It protects your proprietary information from being incorporated into the model’s general training data set. However, without access to your organizations’ context, LLMs (and by extension AI agents) typically produce responses that are inaccurate, irrelevant, or misaligned with your policies and standards.
That’s why best-in-class AI agents combine LLMs with advanced context using techniques like:
This ensures responses are:
This approach has already unlocked a wide range of use cases, and with MCP, the possibilities expand even further.
MCP is an open protocol, introduced by Anthropic and now adopted by OpenAI , that standardizes how AI agents provide context to LLMs.
Think of it as the USB-C port for AI agents: a universal and standardized way to connect the LLMs to different data sources and tools, thus making it easier to feed the right context to the model. This is highly beneficial, because just like the USB-C port did for devices, the MCP will reduce the need to build custom integrations for every single data source such as CRM, billing, logistics, and more.
When a customer asks your AI agent a question, there’s often critical context needed to provide an accurate, helpful answer. MCP defines a standard way for AI agents to fetch that context—securely, reliably, and in real time.
Here’s a closer look at the flow:
With MCP, you can plug any MCP-compliant data source into your AI agent—giving it the ability to reason and act like a true teammate , not just a generic Q&A bot.
Experience the most human AI in action, watch live demos of an AI agent learning and adapting, and learn how leading brands scale with empathy.
Watch on-demandExceptional CX isn’t just about answering quickly—it’s about answering quickly and correctly. Inconsistent or inaccurate responses erode trust and drive costly escalations. MCP empowers AI agents to easily leverage rich customer data and internal policies to resolve more inquiries autonomously, reduce escalations, and build greater customer trust.
Here are some of the ways MCP can empower your AI agent to take on more complex tasks—and operate like a true teammate, not just a tool.
MCP represents a foundational shift for AI agents. Just as APIs unlocked the modern web by establishing a common language that allowed software systems to talk to one another, MCP could become the de facto standard for AI applications and models to leverage organization-specific data—evidenced by the emergence of companies like Stripe, Zapier, and Shopify building MCP servers.
For CX leaders, the potential is massive: adaptive flows that evolve with customer behavior, instant billing clarity, and truly personalized recommendations—delivered by AI agents that understand the full context of each interaction.
As MCP adoption grows, aligning your architecture now means you’ll be ready to deploy smarter, more grounded agents that don’t just respond—they resolve.
Unlock smarter, more grounded customer service. If you’re building an MCP server, we can help you connect it to Ada. Reach out to see what's possible.
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