Enterprise MCP Gateway: Securely Run MCP Behind the Firewall

Model Context Protocol provides a standard for AI assistants to access enterprise systems but leaves identity, authorization, and auditing largely to implementers, creating governance challenges when agents can retrieve data or trigger actions. An enterprise MCP gateway addresses these gaps by serving as a centralized control layer between agents and MCP servers, handling authentication, identity propagation, role-based access, routing, rate limits, policy enforcement, and unified audit logs across multiple systems. The text argues that gateways reduce the complexity and security risks of direct agent-to-tool integrations, prevent credential sprawl and token passthrough, enforce least-privilege access, and preserve each user’s identity at runtime so downstream systems apply their existing permissions and record accurate activity. It highlights requirements such as per-client consent, token audience validation, HTTPS, SIEM-exportable logging, workspace isolation, and integration with OAuth, SAML, and identity-provider lifecycle management. CData Connect AI Gateway is presented as an example platform offering these capabilities, including private cloud connectors that keep on-premises systems behind firewalls through outbound-only connections while supporting managed, private, and hybrid deployment models.

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