What you'll learn:
- Understand why MCP exists, what problem it solves, and how it replaces the n×m integration problem with a single open standard.
- Explain the three MCP roles precisely: Host, Client, and Server, and why this distinction defines every security boundary.
- Describe how an MCP session begins, how capabilities are negotiated, and how dynamic capability updates change the security picture.
- Identify the four core MCP primitives: Tools, Resources, Prompts, and Roots, and understand the governance implications of each.
- Apply MCP's security model: host-owned consent and credentials, OAuth 2.1 with PKCE, and the forbidden patterns to avoid.
- Recognize prompt injection via tool descriptions as an attack vector and apply the controls that mitigate it in production.
- Distinguish MCP from A2A, native function calling, and other connectivity protocols using a clear decision framework.
- Design audit trails for MCP traffic that reconstruct what crossed, who called what, and whose credentials were used.
- Navigate MCP obligations under the EU AI Act, ISO 42001, and the NIST AI Risk Management Framework for deployers.
- Avoid the five most common organizational mistakes with MCP and assess your readiness using a structured maturity checklist.
Every AI application has the same hidden problem. The model can reason, write, and plan, but it cannot touch anything on its own. It cannot read a file, query a database, check a calendar, or search the web. Everything it does in the world happens through connections to external systems, and until recently, every one of those connections had to be built by hand, with custom authentication, custom permissions, and custom logging invented separately every time.
The Model Context Protocol exists to fix that. MCP is the open standard that defines how any AI application connects to any external tool, data source, or system. One protocol, implemented once on each side, replacing an unmanageable web of private, inconsistent, invisible integrations with a single language that can be secured, audited, and governed in one place.
This course gives you a complete, non-technical understanding of MCP and the governance frameworks you need to deploy it responsibly. No programming required. No engineering background needed. Just clear, structured knowledge for the professionals whose job is to ensure AI systems connect to enterprise data safely, with full accountability and regulatory compliance.
You will learn how MCP is organized through its three roles of Host, Client, and Server, and why that distinction defines every security boundary in the protocol. You will explore the four core primitives of Tools, Resources, Prompts, and Roots, and understand the governance implications of each. You will learn how sessions are established, how capabilities are negotiated, and how dynamic updates change the security picture.
The course goes deep on security: MCP's consent and credential model, OAuth 2.1 with PKCE, the forbidden patterns that create systemic risk, prompt injection via tool descriptions as an attack vector, and the procedures for vetting and approving servers before they reach production.
You will learn how MCP compares to A2A, native function calling, and other connectivity protocols, and develop a clear decision framework for choosing the right connector for each job. The final sections cover deployment architectures, audit trail design, registry governance, and the full regulatory landscape including the EU AI Act, ISO 42001, and the NIST AI Risk Management Framework as they apply to MCP deployments.
No technical background required. Just the responsibility of governing AI systems that are connecting to more enterprise data, more tools, and more sensitive systems every month.
