Model Context Protocol (MCP) enables standardized AI agents, but real adoption depends on how MCP servers operate in production—not just how the protocol is defined.

This session provides a high-level, practitioner perspective on running MCP in enterprise environments. It covers how MCP servers fit into existing platforms, with a focus on observability, security, distributed tracking of agent behavior, and resiliency. Rather than diving deep into implementation details, the talk shares lessons learned from real deployments and common pitfalls teams face when moving MCP from experimentation to production.