MCP for Enterprise Knowledge Management: Real-Time Control

Model Context Protocol (MCP) is presented as an open standard for giving AI assistants live, permission-aware access to enterprise systems such as support platforms, HR libraries, documentation repositories, contracts, and data warehouses, rather than relying on periodically synced copies of information. Its host-client-server architecture supports isolated connections to individual data sources, enabling organizations to apply source-system permissions, passthrough user identity via SSO mechanisms such as OAuth, SAML, and OpenID Connect, and query-level audit logging. The text contrasts this approach with traditional knowledge management repositories, which can provide outdated answers or retain access after permissions change, while noting that MCP complements retrieval-augmented generation by standardizing live access to the systems from which RAG retrieves context. It argues that MCP is especially useful for mid-sized and large organizations with multiple governed data sources, established identity infrastructure, compliance requirements, and existing AI deployments, while simpler static retrieval may suffice for smaller environments. CData Connect AI is described as a managed MCP platform intended to centralize connector maintenance, access scoping, identity controls, and SIEM-exportable auditing across hundreds of enterprise sources.

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