Get in Touch

Course Outline

Foundations of the Model Context Protocol

  • Understanding MCP and its role in enabling enterprise AI agent integration.
  • Core concepts including clients, servers, tools, resources, and prompts.
  • Enterprise use cases and the positioning of MCP within the architectural landscape.
  • Comparing MCP with custom integrations and API-only approaches.

Architecting the Enterprise MCP Platform

  • Identifying core platform components, interaction flows, and trust boundaries.
  • Exploring centralized versus distributed integration models.
  • Designing for reuse, control, and clear separation of responsibilities.
  • Aligning MCP with existing enterprise architecture standards and platforms.

Integration Patterns for Systems and Tools

  • Connecting agents to business applications, data services, and internal tools.
  • Patterns for exposing tools, accessing resources, and routing requests.
  • Addressing legacy systems, service boundaries, and integration constraints.
  • Designing robust interfaces and contracts to ensure reliable interoperability.

Security, Access Control, and Governance

  • Implementing authentication, authorization, and least-privilege design.
  • Ensuring data protection, policy enforcement, and auditability.
  • Establishing guardrails for tool usage and sensitive resource access.
  • Defining governance roles, approval processes, and compliance requirements.

Operations, Deployment, and Adoption Planning

  • Monitoring platform health, usage metrics, and failure points.
  • Managing versioning, lifecycle management, and change control.
  • Evaluating cloud, on-premise, and hybrid deployment considerations.
  • Developing a practical rollout roadmap and defining the target operating model.

Architecture Workshop

  • Analyzing a realistic enterprise AI integration scenario.
  • Identifying key risks, necessary controls, and critical architecture decisions.
  • Drafting a reference architecture for a secure MCP-based agent platform.
  • Presenting design choices and outlining subsequent steps.

Requirements

  • Solid understanding of enterprise architecture and system integration principles.
  • Familiarity with APIs, cloud or on-premise platforms, and fundamental security controls.
  • Prior experience in technical solution design or architecture planning.

Audience

  • Enterprise architects and solution architects.
  • AI platform architects and technical leads.
  • Stakeholders involved in integration, security, and governance for enterprise AI initiatives.
 7 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories