What is an Agent Sandbox?
An agent sandbox is a controlled environment that constrains which tools an AI agent can access and how it can use them — preventing the agent from affecting systems outside its authorised scope.
WHY IT MATTERS
You would not deploy untested code to production without constraints. You should not deploy untested agents with unrestricted tool access. Sandboxes provide boundaries where agents can operate without the ability to cause unintended harm.
Agent sandboxing via policy enforcement is more flexible than traditional isolation. Rather than running agents in isolated containers (which limits their usefulness), policy-based sandboxing lets agents connect to real systems but restricts what they can do with those systems.
For example, a sandboxed coding agent might have read access to the entire codebase but write access only to a feature branch directory, with shell execution limited to test commands. The agent interacts with real systems but within tightly controlled boundaries.
HOW POLICYLAYER USES THIS
Intercept creates tool-level sandboxes through YAML policies. Define which tools the agent can access, constrain arguments to safe values, and enforce rate limits — all without modifying the agent or the MCP server. A restrictive policy effectively sandboxes the agent: it can only do what the policy permits, nothing more. Fail-closed by default means any tool not explicitly allowed is denied.