The emergence of Anthropic's Model Context Protocol (MCP) has led to confusion among developers and product managers, with some viewing it as a replacement for APIs, while others see it as inferior. However, the reality is that MCP and APIs are complementary, with many well-designed AI systems needing both. MCP provides a standardized way for large language models to interact with external data sources through existing APIs, managing context between them, while APIs handle core data transmission, authentication flows, and connections to different applications. The combination of MCP's context management capabilities with robust API infrastructure is necessary to address security challenges, such as access control and data loss prevention. Ultimately, understanding the relationship between MCP and APIs will give companies a competitive advantage in building sophisticated AI assistants, and recognizing when to leverage each will depend on the specific scenario and the complexity of the system being built.