Control and Secure Data for AI with Customizable APIs

Model Context Protocol (MCP) makes it easier for AI systems to access live enterprise data and perform actions, but direct database connections can create risks such as destructive queries, exposure of sensitive information, excessive costs, and insufficient auditing. The proposed approach is to place APIs between AI platforms and internal data systems, creating a curated interface that limits the data, operations, credentials, and permissions available to AI while enforcing governance controls. CData positions its API Server and MCP Server as a solution for exposing real-time database, warehouse, and structured-system data through configurable API endpoints that inherit existing access permissions and support role- and object-level controls, rate limiting, IP restrictions, and centralized logging. Organizations can deploy the tools locally, define endpoints with filtering, authorization rules, and clearer field names, then connect AI frameworks through an MCP middleware layer without necessarily making APIs internet-facing. The offering is presented as a way to combine AI-driven insights with current data while maintaining security, compliance, and operational control, with a free trial and setup guide available.

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