search_by_series_uid
AI agents call search_by_series_uid 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 tool name strongly implies a search operation, which is a Read category action (queries data without side effects). The absence of any destructive, write, or execute indicators in the name, combined with the 'search' verb, points to data retrieval. However, confidence is moderate (0.6) due to the empty description, which prevents definitive assessment of the tool's exact behavior and scope.
From the tool's definition Tool name 'search_by_series_uid' indicates a query/search operation. Description is empty, which reduces confidence. The naming convention ('search_*') suggests data retrieval rather than modification.
Attacks that exploit this kind of access
search_by_series_uid. 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_by_series_uid: 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_by_series_uid 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_by_series_uid 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_by_series_uid. 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_by_series_uid 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.