We have seen the Model Context Protocol (MCP) unlock incredible agentic workflows, but there is a hard truth we always tell our clients: building the technical architecture is the easy part. The gap between “it works perfectly in my demo” and “the enterprise security team approves it for production” is where most MCP projects die. To get your AI agents out of the sandbox and into production, you need to design for security, governance, and enterprise reality from day one. Here is a pragmatic talk on the security considerations and best practices I use for enterprise MCP development.

We go through topics like IAM, data access, human-in-the-loop, operational guardrails, supply chain vulnerabilities, and dependency management.