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Course Outline

Fundamentals of the Model Context Protocol

  • Overview of MCP and its role in facilitating enterprise AI agent integration for government
  • Essential components, including clients, servers, tools, resources, and prompts
  • Enterprise applications and MCP’s position within the broader architecture landscape
  • Comparison of MCP against custom integrations and API-centric solutions

Constructing Enterprise MCP Architecture

  • Core platform elements, interaction workflows, and trust boundaries
  • Evaluation of centralized versus distributed integration models for government operations
  • Strategies to promote reusability, oversight, and clear separation of duties
  • Alignment of MCP with established enterprise architecture standards and platforms

Integration Patterns for Systems and Tools

  • Methods for connecting agents to business applications, data services, and internal tools
  • Approaches for tool exposure, resource accessibility, and request routing
  • Strategies for addressing legacy systems, service boundaries, and integration constraints
  • Establishing clear interfaces and contracts to ensure reliable interoperability

Security, Access Control, and Governance

  • Implementation of authentication, authorization, and least-privilege principles
  • Measures for data protection, policy enforcement, and auditability
  • Establishment of guardrails for tool usage and access to sensitive resources
  • Definition of governance roles, approval workflows, and compliance requirements for government entities

Operations, Deployment, and Adoption Planning

  • Strategies for monitoring usage, failures, and platform health
  • Management of versioning, lifecycle processes, and change control
  • Considerations for cloud, on-premise, and hybrid deployment environments
  • Development of a practical rollout roadmap and target operating model

Architecture Workshop

  • Analysis of a realistic enterprise AI integration scenario relevant to government needs
  • Identification of key risks, controls, and critical architecture decisions
  • Formulation of a reference architecture for a secure MCP-based agent platform for government use
  • Presentation of design choices and definition of subsequent action items

Requirements

  • Comprehensive knowledge of enterprise architecture principles and system integration frameworks.
  • Proficiency with application programming interfaces (APIs), cloud-based or on-premises infrastructures, and fundamental security protocols.
  • Demonstrated experience in the design of technical solutions and participation in architectural reviews.

Audience

  • Enterprise architects and solution architects.
  • Architects and technical leads specializing in AI platforms.
  • Stakeholders responsible for integration, security, and governance within enterprise AI initiatives designed for government applications.
 7 Hours

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