This whitepaper provides a comprehensive framework for securing Model Context Protocol (MCP) architectures used in AI data connectivity, addressing emerging risks such as prompt injection, credential misuse, and supply chain vulnerabilities. It emphasizes a managed platform approach, highlighting identity-first security, in-place data access, and centralized governance as core principles, as outlined in the architecture sections on pages 4–5. The guide details best practices including RBAC passthrough, SSO integration, OAuth 2.1 with PKCE, and SCIM-based identity lifecycle management to enforce least-privilege access. It also introduces layered controls such as workspaces, derived views, and custom tools to limit data exposure while maintaining flexibility. Comprehensive audit logging, inc

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