Could SQL Access Replace Endless API Endpoints for AI Agents?

As AI agents grow more capable, traditional REST API architectures are struggling to keep up with complex, relational data queries from users. Building a financial platform API, for example, quickly balloons from a handful of endpoints into hundreds of hyper-specific routes, each requiring its own OpenAPI specification, error handling, and maintenance overhead. Every new user query pattern — such as filtering transactions by card expiry or linking accounts to documents — demands yet another bespoke endpoint. This proliferation creates long-term maintenance nightmares and forces clients to stitch together multiple API responses to answer simple questions. The article explores whether allowing AI agents to run SQL-style queries directly on user data could offer a more scalable and flexible alternative to the endpoint-per-question model.