Why I Don't Use MCP for AI in My SaaS: Architectural Tradeoffs
Hintway · reddit · 2026-08-11
The author explains why they avoided MCP for their analytics SaaS. Since the product already has a robust backend with authentication, tenant isolation, and audit trails, they want the AI to work within this architecture rather than bypass it.
Alternative Approach:
- The backend creates AI sessions with specific user permissions and tenant context.
- The model calls typed application tools (e.g., safe aggregates, exports) that enforce existing business logic and security.
- Prism orchestrates tool calls, ensuring the model never gets direct DB access.
They argue MCP is great for external integrations, but for core SaaS workflows, typed application tools offer better security, auditing, and ownership.
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