Stop dangerous agent actions before they happen.
Boundary is a predictive security layer for autonomous AI agents and MCP systems. It reasons about what an action makes possible next — not only whether the current action is allowed.
Traditional security checks the action.
Boundary checks the future it creates.
Agentic systems can chain individually legitimate actions into a dangerous outcome. Boundary reasons across information flows, capabilities, derivations and communication paths to detect when a prohibited state becomes reachable.
Model
Describe agents, capabilities, information flows, communication paths and safety invariants.
Predict
Before execution, Boundary determines what future states the proposed action can make reachable.
Enforce
Allow safe actions, require human approval for predictive risk, and block prohibited behavior.
Put Boundary in front of the tools you already use.
Boundary discovers tools from an existing MCP server, mirrors their interface and evaluates each modeled action before it is forwarded upstream.
Reason about prohibited future states before the final harmful action.
Pause predictively risky actions and require explicit one-shot approval.
New or unmodeled upstream capabilities cannot silently bypass the security model.
Record enforcement, approvals and execution decisions for investigation and governance.
Help us test Boundary on real agent systems.
We're inviting a small number of AI and security teams building with MCP and autonomous agents to test the first external alpha.