AWS Engineers Warn of Hidden Costs and Complexity When Scaling MCP Agents to Production

Deploying Model Context Protocol (MCP) servers beyond local demos exposes serious operational challenges, including unpredictable autoscaling, per-session IAM role management, and runaway token costs that often go unnoticed until monthly invoices arrive. AWS offers two managed alternatives to self-managed containers: Amazon Bedrock AgentCore Runtime for serverless agent hosting and AgentCore Gateway for converting existing APIs into governed MCP-compatible tools without writing new servers. Unlike traditional services, misbehaving agents rarely throw errors — they silently retry or loop through tool calls, quietly accumulating costs with no immediate alert. Engineers recommend tagging spend at the session or tenant level to accurately attribute costs per agent run, rather than relying on broad service-level metrics. Strict rate limiting at the gateway layer and distributed tracing of agent decision paths — not just request paths — are highlighted as essential safeguards before any production rollout.