Enables real-time user intervention for MCP agents via a Web UI and interactive_feedback tool, allowing users to review context and send instructions when agents drift from intent.
A governance and control layer for MCP tools that manages tool requests as intents through policy-based approval, queuing, or blocking. It enables secure human oversight and audit trails for consequential agent actions across platforms like Claude Desktop and Cursor.
Pre-execution governance for AI agents. 45 MCP tools for hold queues, audit trails, risk scoring, and policy enforcement. Validates agent actions before they execute.