Agentic AI tooling: Why runtime security is the missing layer

A developer asks an AI coding agent to refactor a microservice. Within seconds, the agent opens source files, executes shell commands, calls external APIs, and modifies cloud configuration. No human approves each step. No security tool monitors what the agent does between receiving the prompt and delivering the result. This is not theoretical. Over the past year, researchers and security teams have disclosed a growing set of real-world attacks against agent infrastructure (from MCP tool poisoning to credential theft through coding agents) and industry surveys consistently find that most organizations have little visibility into the machine-to-machine traffic their agents generate. The tooling ecosystem powering these agents is maturing fast. The security controls governing them are not. Model Context Protocol (MCP): Standard interface for agents to discover and interact with external systems, each exposing a set of tools (callable functions the agent can…