What the Model Context Protocol means for customer service

The Model Context Protocol is an open standard that lets AI systems interact with external tools and data sources through a unified interface. Think of it as USB for AI — a single connector that works with any system that implements it.

For customer service, this is transformative.

The integration problem

Every B2B company runs on a stack of specialised systems. ERP for orders and inventory. CRM for customer relationships. A logistics platform for shipping. An invoicing system. A product information management system.

When a customer asks a question, the answer usually lives across two or three of these systems. A human agent navigates between them, copying and pasting, cross-referencing, and synthesising an answer.

Traditional integrations are point-to-point: build a connector between system A and system B, maintain it when either changes, repeat for every combination. This does not scale.

How MCP changes the equation

With MCP, each business system exposes its capabilities as a set of tools — structured functions that an AI agent can discover and call.

// An MCP server for an ERP might expose:
get_order({ order_id: "ORD-2024-1847" })
search_orders({ customer_id: "C-500", status: "delayed" })
get_delivery_schedule({ order_id: "ORD-2024-1847" })

The AI agent does not need to know how the ERP works internally. It discovers what tools are available, understands their parameters, and calls them as needed to resolve the query.

What this means in practice

Consider a customer email asking about a delayed order:

1. The agent reads the email and identifies the intent: order status inquiry
2. It calls search_orders on the ERP MCP server to find the order
3. It calls get_delivery_schedule to get the current expected date
4. It calls get_compensation_policy on the policy MCP server to check if delay compensation applies
5. It composes a response with all the relevant information

No human touched the query. No custom integration code was written for this specific workflow. The agent composed the resolution from available tools.

The compounding benefit

Every new MCP server you connect expands what the agent can resolve autonomously. Connect your returns system, and return queries become resolvable. Connect your quoting system, and quote requests become resolvable.

oHallo does not need to understand what a return or a quote is. It discovers the tools, understands their descriptions, and uses them when relevant.

This is fundamentally different from traditional automation, where every new capability requires explicit programming. With MCP, capability grows with connectivity.