AI agents call get-queue-bindings to retrieve information from Rabbitmq without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and lists existing queue bindings without creating, modifying, or deleting any data. It has no side effects and poses minimal risk if called by an AI agent. Classification as Read is appropriate for informational queries on RabbitMQ infrastructure.
From the tool's definition Tool name contains 'get' and description states 'List queue bindings' — both indicate a retrieval/query operation with no modification of state.
Attacks that exploit this kind of access
List queue bindings. It is categorised as a Read tool in the Rabbitmq MCP Server, which means it retrieves data without modifying state.
Register the Rabbitmq MCP server in PolicyLayer and add a rule for get-queue-bindings: 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 Rabbitmq. Nothing to install.
get-queue-bindings is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the get-queue-bindings 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 get-queue-bindings. 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.
get-queue-bindings is provided by the Rabbitmq MCP server (rabbitmq-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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