This paper explains agentic AI as a shift from passive, prompt-based models to autonomous agents that reason, retain memory, and take action by calling APIs across enterprise systems. These agents rely on LLMs for reasoning and MCP servers to orchestrate tools, memory, and context, making APIs the execution layer for decisions and workflows. While agentic AI is already being deployed in sectors like finance, healthcare, and travel, it introduces new risks tied to autonomy, persistent memory, and machine-driven API traffic. Traditional security tools lack visibility into agent intent, API chaining, memory misuse, and rogue agents or MCP servers. The paper argues that securing agentic AI requires securing the API fabric itself, with visibility and control over agent behavior, tool usage, and

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