Get in Touch
 Duration 7 hours

Course Outline

Core Principles of the Model Context Protocol

  • Definition of MCP and its role in facilitating enterprise AI agent connectivity
  • Foundational elements including clients, servers, tools, resources, and prompt structures
  • Application scenarios and architectural positioning of MCP within enterprise environments
  • Comparison between MCP and bespoke integration strategies or API-centric models

Formulating an Enterprise-Grade MCP Architecture

  • Essential platform elements, data interaction pathways, and security perimeters
  • Strategic choices between centralized and decentralized integration frameworks
  • Architectural design focused on modularity, regulatory control, and functional segregation
  • Alignment of MCP standards with established enterprise architectural guidelines

Integration Frameworks for Corporate Systems and Utilities

  • Linking AI agents with business applications, data repositories, and internal instruments
  • Methodologies for exposing tools, managing resource access, and directing requests
  • Navigating legacy infrastructure, service limitations, and integration hurdles
  • Defining precise interfaces and protocols to ensure stable interoperability

Security Protocols, Access Management, and Regulatory Oversight

  • Implementation of authentication, authorization, and least-privilege access policies
  • Data safeguards, enforcement of administrative policies, and audit trail integrity
  • Establishing controls for tool utilization and protection of sensitive assets
  • Defining governance responsibilities, approval workflows, and compliance alignment

Operational Management, Deployment Strategy, and Adoption Planning

  • Surveillance of system usage, error monitoring, and platform stability
  • Version control, lifecycle administration, and rigorous change management
  • Considerations for cloud-based, on-premises, and hybrid deployment models
  • Development of a phased rollout strategy and long-term operational model

Architectural Design Workshop

  • Analysis of a representative enterprise AI integration case study
  • Identification of critical risks, mitigation controls, and architectural decisions
  • Creation of a reference architecture for a secure, MCP-based agent platform
  • Presentation of design selections and establishment of subsequent actions

Requirements

  • Understanding of enterprise architecture and system integration concepts
  • Familiarity with APIs, cloud or on-premise platforms, and basic security controls
  • Experience in technical solution design or architecture discussions

Audience

  • Enterprise architects and solution architects
  • AI platform architects and technical leads
  • Integration, security, and governance stakeholders involved in enterprise AI initiatives

Number of participants


Price per participant

Upcoming Courses

Related Categories