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Course Outline
MCP Fundamentals and Business Value
- What MCP is and why organizations are adopting it
- Problems MCP helps solve in AI integration
- MCP compared with direct API integration and other tool connection approaches
- Common enterprise use cases and expected benefits
Core Architecture and Components
- Roles of hosts, clients, and servers
- How tools, resources, and prompts are used
- Request and response flow in a typical MCP interaction
- Local and remote deployment patterns
Setting Up a Basic MCP Workflow
- Preparing the working environment
- Reviewing a simple MCP server configuration
- Connecting a client to an MCP server
- Running and validating a basic workflow
Designing Useful MCP Integrations
- Selecting the right capability for a business scenario
- Structuring tools for safe and useful actions
- Using resources to provide relevant context
- Using prompts to improve consistency and usability
Security, Governance, and Operations
- Access control, permissions, and authentication considerations
- Handling sensitive business data safely
- Trust, approval, and oversight practices
- Monitoring, maintenance, and operational good practices
Implementation Planning and Next Steps
- Identifying realistic use cases for an initial rollout
- Key design decisions and practical trade-offs
- Planning adoption in enterprise environments
- Course review, summary, and next steps
Requirements
- Basic understanding of AI assistants, APIs, and business application workflows
- Experience using web applications, developer tools, or enterprise software platforms
- Basic technical or programming experience
Audience
- AI engineers and application developers
- Solution architects and technical leads
- Product teams and IT professionals evaluating AI integration options
7 Hours
