listDatabases
AI agents call listDatabases 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 combined with 'Databases' indicates this tool queries or enumerates SageMaker databases without modifying them. While the empty description reduces confidence slightly, the semantic intent is clearly a Read operation. Severity is medium because unauthorized database enumeration could reveal sensitive infrastructure details in a SageMaker environment, but it does not modify, delete, or execute code.
From the tool's definition Tool name 'listDatabases' indicates a listing/enumeration operation typical of Read category tools. The empty description limits certainty, but the 'list' prefix strongly suggests data retrieval without side effects.
Attacks that exploit this kind of access
listDatabases. 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 listDatabases: 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.
listDatabases 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 listDatabases 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 listDatabases. 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.
listDatabases 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.