Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 7 hours
Course Outline
Foundations of the Model Context Protocol
- Understanding what MCP is and how it enables enterprise AI agent integration
- Core concepts including clients, servers, tools, resources, and prompts
- Enterprise use cases and the role of MCP within an architecture landscape
- Comparing MCP with custom integrations and API-only approaches
Designing the Enterprise MCP Architecture
- Key platform components, interaction flows, and trust boundaries
- Centralized versus distributed integration models
- Designing for reusability, 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 tool exposure, resource access, and request routing
- Managing legacy systems, service boundaries, and integration constraints
- Designing clear interfaces and contracts for reliable interoperability
Security, Access Control, and Governance
- Authentication, authorization, and least-privilege design principles
- Data protection, policy enforcement, and audit trails
- Implementing guardrails for tool usage and access to sensitive resources
- Governance roles, approval workflows, and compliance considerations
Operations, Deployment, and Adoption Planning
- Monitoring usage, failures, and overall platform health
- Versioning, lifecycle management, and change control processes
- Considerations for cloud, on-premise, and hybrid deployment environments
- Developing a practical rollout roadmap and target operating model
Architecture Workshop
- Analyzing a realistic enterprise AI integration scenario
- Identifying key risks, controls, and critical architecture decisions
- Drafting a reference architecture for a secure, MCP-based agent platform
- Presenting design choices and outlining next steps
Requirements
- A solid understanding of enterprise architecture and system integration concepts
- Familiarity with APIs, cloud or on-premise platforms, and fundamental security controls
- Experience in designing technical solutions or participating in architecture discussions
Target Audience
- Enterprise architects and solution architects
- AI platform architects and technical leads
- Integration, security, and governance stakeholders involved in enterprise AI initiatives
