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Duration 7 hours
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 utilized.
- 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 appropriate 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 best 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
- Fundamental understanding of AI assistants, APIs, and business application workflows.
- Experience with web applications, developer tools, or enterprise software platforms.
- Basic technical or programming background.
Audience
- AI engineers and application developers.
- Solution architects and technical leads.
- Product teams and IT professionals evaluating AI integration options.
