From POC to Production: Running MCP in the Enterprise(US)

MCP is simple in a demo. An agent calls a tool. A CRUD API runs. A response comes back. Clean. Fast. Contained.

But in the enterprise, that same call doesn’t just return data — it can disable payroll, revoke access, page the wrong on-call team, corrupt CRM records, or trigger compliance audits. When AI agents move from sandbox to production, the operating model changes entirely.

But does it really take to run MCP in the enterprise — and why lightweight MCP servers are not enough? We’ll unpack how Workato Enterprise MCP acts as a unified control plane for AI, where every tool call maps to a resilient, multi-step orchestrated workflow with validation, branching, approvals, compensation logic, and full traceability.

We’ll dive into the core components required for production-grade MCP: governance and policy enforcement, authentication and authorization, throttling and context-aware limits, token cost controls, registry and discovery mechanisms, and deep observability with step-level audit trails and analytics.

If your agents are touching critical systems, you need more than APIs — you need orchestration, security, and operational discipline.

Join us this Product Hour to learn how to build MCP for real enterprise consequences — not just demo-day simplicity.

What You Will Learn?

• What happens with AI goes rogue?
• Designing MCPs for production
• Enforcing security and governance
• Observability: why seeing is trusting 
• Live demos and real use cases