When to use (and not use) Model Context Protocol

Model Context Protocol (MCP) is gaining popularity as it allows developers to connect Large Language Models (LLMs) to external tools and data sources for orchestrating complex tasks, particularly through APIs and third-party systems. While MCP offers flexibility and rapid development for low-stakes projects or prototypes by enabling natural language workflow creation, it poses challenges when used as a foundation for applications. Concerns include the risk of embedding critical business logic within prompt chains, potential data governance issues by exposing sensitive customer data to LLM providers, and the dilution of product ownership. Unified.to advocates for a balanced approach where LLMs enhance specific functionalities while maintaining control over data access and orchestration, promoting AI-native architectures that integrate structured data and unified APIs for sustainable and reliable SaaS products.