DeepKeep for AI Agents is a security platform designed to monitor, evaluate, and control AI agent activity in enterprise environments. The platform addresses security challenges associated with AI agents that initiate tasks, interact with large language models, process data, and coordinate with other agents. The platform provides visibility into agent behavior by tracking data flows, system interactions, and decision-making structures. It identifies vulnerabilities and unsafe design patterns in agent architectures, offering recommendations for remediation before security incidents occur. DeepKeep includes capabilities for enforcing Model Context Protocol (MCP) server usage. The platform monitors and evaluates gateway usage, identifies which MCP servers are being accessed by agents, and provides recommendations on whether to allow or block specific servers. Organizations can enforce consistent policies across their AI agent deployments. The platform highlights security risks by assessing agent activity patterns and identifying potential threats. It provides context-aware controls that enable security teams to intervene in agent operations when necessary. The system aims to eliminate blind spots in AI agent security by offering comprehensive visibility into agent behavior across enterprise environments.