List all Timestream for InfluxDB instances belonging to a specific DB cluster.
AI agents call LsInstancesOfCluster to retrieve information from Amazon SageMaker AI MCP Server 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 instances from a database cluster. It performs a read-only query operation that retrieves data without creating, modifying, deleting, or executing anything. The blast radius of misuse is minimal since it only exposes informational data about existing cluster instances.
From the tool's definition Tool name and description indicate 'List all Timestream for InfluxDB instances' - a query/enumeration operation with no modification or side effects.
Attacks that exploit this kind of access
List all Timestream for InfluxDB instances belonging to a specific DB cluster. It is categorised as a Read tool in the Amazon SageMaker AI MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Amazon SageMaker AI MCP Server MCP server in PolicyLayer and add a rule for LsInstancesOfCluster: 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 Amazon SageMaker AI MCP Server. Nothing to install.
LsInstancesOfCluster 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 LsInstancesOfCluster 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 LsInstancesOfCluster. 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.
LsInstancesOfCluster is provided by the Amazon SageMaker AI MCP Server MCP server (awslabs.sagemaker-ai-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.