ListKnowledgeBases
AI agents call ListKnowledgeBases 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.
List operations in AWS services retrieve and enumerate resources without modifying, deleting, or executing operations. The 'List' prefix is a standard AWS convention for read-only operations. Despite the empty description reducing confidence slightly, the naming pattern is highly indicative of a Read category tool with low severity and minimal blast radius if misused by an AI agent.
From the tool's definition Tool name 'ListKnowledgeBases' follows the 'List' pattern, indicating data retrieval. The description is empty, but naming convention strongly suggests a read-only query operation typical of AWS API list operations.
Attacks that exploit this kind of access
ListKnowledgeBases. 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 ListKnowledgeBases: 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.
ListKnowledgeBases 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 ListKnowledgeBases 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 ListKnowledgeBases. 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.
ListKnowledgeBases 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.