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Mastering Model Context Protocol for Production AI
Chapters

1Foundations of Model Context Protocol

2Data Modeling for MCP

3Data Pipelines and MCP

4Context-Aware Prompt Engineering

5Model Selection and Architecture for MCP

6Evaluation, Testing, and Validation of MCP

7Deployment Patterns and Runbooks

8Monitoring, Observability, and Reliability

9Privacy, Security, and Compliance in MCP

Data minimization in contextConsent management for contextual dataAccess control and least privilegeEncryption at rest and in transitAudit logging and provenanceGDPR/CCPA considerationsPII handling in contextData retention and deletion policiesPrivacy-by-design in MCPThreat modeling for context systemsSecure multi-party computation for MCPSecure APIs and tokensIncident response for data breachesVendor risk managementCompliance automation and tooling

10Ethics, Governance, and Responsible AI in MCP

11Real-World Case Studies and Industry Applications

12Capstone Project and Roadmap

Courses/Mastering Model Context Protocol for Production AI/Privacy, Security, and Compliance in MCP

Privacy, Security, and Compliance in MCP

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Protect user privacy and comply with regulatory requirements while enabling MCP capabilities in production environments.

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Data minimization in context

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