list_datastores
AI agents call list_datastores 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.
The 'list_' prefix is a standard pattern for read-only operations that enumerate or query resources without modification. In the context of a SageMaker AI server, listing datastores would retrieve metadata about existing data storage resources without creating, modifying, or deleting them. The empty description prevents full certainty, but the name alone provides sufficient evidence for a Read classification.
From the tool's definition Tool name 'list_datastores' indicates a listing/retrieval operation with no side effects. The empty description reduces confidence slightly, but the naming convention strongly suggests a read-only data retrieval action consistent with AWS SageMaker data…
Attacks that exploit this kind of access
list_datastores. 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 list_datastores: 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.
list_datastores 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 list_datastores 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 list_datastores. 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.
list_datastores 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.