Enterprise AI Needs More than MCP Gateways

Model Context Protocol (MCP) standardizes how large language models request actions from external services, but it does not itself define the security, governance, or operational controls needed to expose enterprise systems safely. While MCP gateways can centralize routing, discovery, rate limiting, and basic access management, they depend on the security of the underlying MCP servers and may leave organizations responsible for maintaining numerous integrations, credentials, metadata models, audit logs, and high-availability systems. The passage highlights risks from unauthenticated servers, reused credentials, weak agent isolation, and unverified external connections, arguing that enterprise adoption requires secure defaults, centralized policy enforcement, semantic understanding of source data, and complete auditability. It presents CData Connect AI as a managed MCP platform that combines gateway functions with MCP-compliant access to more than 350 enterprise systems, offering prebuilt connectors, identity controls, metadata modeling, and managed infrastructure intended to reduce the complexity and security exposure of independently operated MCP stacks.

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