Wait for multiple AI agent processes to complete and return their results. Defaults to compact result items; set verbose to true for full metadata and detailed parsed output.
AI agents invoke wait to trigger actions in Agent Bridge. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool does not simply retrieve static data (Read), nor does it create/modify reversible data structures (Write). Instead, it actively manages the lifecycle of executing subprocesses and waits for their completion. The underlying processes themselves execute arbitrary AI CLI tasks, which is the definition of Execute.
From the tool's definition The tool 'wait' monitors and manages background subprocess execution of AI CLI tasks (Claude, Codex, Gemini, Forge, OpenCode). It operates on processes launched by the 'run' tool and retrieves their results, indicating active subprocess lifecycle management.
Attacks that exploit this kind of access
Wait for multiple AI agent processes to complete and return their results. Defaults to compact result items; set verbose to true for full metadata and detailed parsed output. It is categorised as a Execute tool in the Agent Bridge MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Agent Bridge MCP server in PolicyLayer and add a rule for wait: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Agent Bridge. Nothing to install.
wait is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the wait rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for wait. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
wait is provided by the Agent Bridge MCP server (lailai258/agent-bridge-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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