Building an MCP server is getting easier. Monetizing one is not.

At first, usage-based billing looks simple: count tool calls, aggregate them monthly, and send an invoice. But once MCP servers move into production agent workflows, the definition of “usage” becomes much harder. Was that one tool call or ten? Should you bill for tokens, API calls, records retrieved, compute time, successful outcomes, or prepaid credits consumed? What happens when an agent retries, chains tools, streams results, or calls the same resource through multiple clients?

In this session, we’ll dive into the infrastructure behind trustworthy metering and pricing for MCP-native products. We’ll cover how to design a billing pipeline that can:

Count usage once and only once, even with retries, failures, and agent loops
Handle high-volume event streams from MCP tool calls
Give customers real-time visibility into current-period usage
Support pay-as-you-go, prepaid credits, drawdown models, and hybrid pricing
Preserve developer trust by making usage explainable and auditable

MCP is often described as a standard way for AI clients to call tools, resources, and prompts across servers. That makes every MCP server a potential commercial surface area: tool calls become billable events, resources become metered access, and agent workflows become revenue streams