search_cdk_samples_and_constructs
AI agents call search_cdk_samples_and_constructs 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 name suggests this tool searches for CDK (AWS Cloud Development Kit) samples and constructs—a retrieval operation with no side effects. Search operations are classified as Read. The empty description reduces confidence slightly, but the verb 'search' and context of CDK samples/constructs (typically reference material) support this classification. No financial, destructive, or code-execution implications evident.
From the tool's definition Tool name 'search_cdk_samples_and_constructs' indicates a search/query operation. Description is empty, limiting certainty.
Attacks that exploit this kind of access
search_cdk_samples_and_constructs. 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 search_cdk_samples_and_constructs: 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.
search_cdk_samples_and_constructs 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 search_cdk_samples_and_constructs 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 search_cdk_samples_and_constructs. 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.
search_cdk_samples_and_constructs 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.