queue_operations
Execute multiple operations in sequence. Operations run in order with result references ($0.field) to chain outputs. Use for multi-step workflows.
This record as markdown: /tools/aaronsb-google-workspace-mcp/queue-operations.md
What queue_operations does on Google Workspace MCP Server
AI agents invoke queue_operations to trigger actions in Google Workspace MCP Server. 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.
Why queue_operations is rated High
This tool is Execute rather than Write because it runs/triggers multiple chained operations whose effects depend on what those operations are and their arguments. While individual operations might be Write, Read, or Destructive, this tool's purpose is to orchestrate execution of sequences of such operations.
From the tool's definition Tool description states 'Execute multiple operations in sequence' and is designed to 'chain outputs' from sequential operations.
Attacks that exploit this kind of access
The rule that runs queue_operations safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Google Workspace MCP Server, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For queue_operations, this is the rule to start with:
queue_operations stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Google Workspace MCP Server, apply this rule, and every queue_operations call is checked against it from then on.
Questions about queue_operations
Execute multiple operations in sequence. Operations run in order with result references ($0.field) to chain outputs. Use for multi-step workflows. It is categorised as a Execute tool in the Google Workspace MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Google Workspace MCP Server MCP server in PolicyLayer and add a rule for queue_operations: 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 Google Workspace MCP Server. Nothing to install.
queue_operations 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 queue_operations 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 queue_operations. 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.
queue_operations is provided by the Google Workspace MCP Server MCP server (aaronsb/google-workspace-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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