The most common misunderstanding is treating MCP as a solution to problems it doesn't touch. It solves a connection problem. It is silent on almost everything else you care about.

MCP Gives You	MCP Does Not Give You
A standard way to connect to tools and data	Any guarantee the agent uses them well
Reuse across AI products	A permission model for your business rules
A growing ecosystem of existing servers	Assurance that a third-party server is safe
Cleaner conversations about capability	Evaluation, monitoring or cost control
Less integration work per connection	Any reduction in the work of designing good tools

The Risk in the Third Row

A convenient ecosystem of ready-made servers is genuinely useful and it introduces a supply-chain question. A third-party server is code running with access to your systems and your data. Treat adding one with the same scrutiny you'd apply to any third-party dependency with production access, because that's exactly what it is. This belongs in your security review, not in a configuration ticket.

Agentic AI and MCP for Product Managers

Module 1What 'Agentic' Actually Means

Module 2How an Agent Actually Works

Module 3MCP: What It Is and Why You Should Care

Module 4Designing the Tool Layer

Module 5Permissions and the Human in the Loop

Module 6Evaluating Agents

Module 7Cost, Latency and Unpredictability

Module 8Designing What the User Sees

Module 9Risk and Blast Radius

Module 10When an Agent Is the Wrong Answer

Module 11Final Project: Design One Real Agent End to End

Module 12Appendix: The Prompt Library

What MCP Gives You and What It Doesn't