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Duration 14 hours
Course Outline
MCP Fundamentals and Enterprise Applications
- Understanding the Model Context Protocol and its role in enterprise AI integration
- Exploring how MCP servers and clients interact with models, tools, and backend systems
- Reviewing common use cases, advantages, and limitations in team-based settings
- Identifying critical design considerations for production adoption
Designing MCP Servers and Clients
- Establishing capabilities, contracts, and distinct responsibilities between server and client components
- Organizing tools, resources, and prompts to ensure maintainability and reuse
- Implementing validation, consistent outputs, and informative error responses
- Crafting workflows that are practical for team ownership and support
Reliability and Security in Production
- Managing failures, invalid requests, and downstream service disruptions
- Utilizing timeouts, retries, fallback strategies, and secure processing patterns
- Applying principles of authentication, authorization, and secret management
- Ensuring auditability and controlled access to enterprise tools and data
Deployment, Observability, and Operations
- Packaging and deploying MCP services across local, containerized, or cloud environments
- Managing configuration, environment variances, and release processes
- Implementing logs, metrics, health checks, and alerting for runtime visibility
- Resolving common operational issues across clients and backend integrations
Testing, Versioning, and Change Management
- Developing unit, integration, and contract tests for MCP workflows
- Managing interface changes and ensuring compatibility over time
- Validating releases prior to rollout to minimize upgrade risks
- Employing practical readiness checks for continuous support and maintenance
Practical Implementation Workshop
- Constructing a basic enterprise-ready MCP server and client workflow
- Applying validation, resilience, security, and observability best practices
- Evaluating a production readiness checklist
- Planning subsequent steps for adoption within internal teams and platforms
Requirements
- Proficiency with APIs, JSON, and fundamental client-server integration concepts
- Experience with command-line tools, Git, and basic application deployment workflows
- Foundational programming experience in Python, JavaScript, or a comparable language
Audience
- Software developers creating MCP-enabled applications and integrations
- Solution architects and technical leads accountable for enterprise AI integration
- Platform, DevOps, and engineering teams responsible for supporting production MCP services
