SearchRelevantContent
AI agents call SearchRelevantContent 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.
Search operations typically retrieve or query data without side effects. While the empty description reduces confidence, the naming convention strongly implies a Read-category tool. No evidence suggests data modification, execution of commands, deletion, or financial operations. The low blast radius of a search query on AWS SageMaker content makes severity low.
From the tool's definition Tool name 'SearchRelevantContent' indicates a search/query operation. The description is empty, which limits certainty, but the verb 'Search' and 'Relevant' combined suggest data retrieval without modification.
Attacks that exploit this kind of access
SearchRelevantContent. 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 SearchRelevantContent: 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.
SearchRelevantContent 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 SearchRelevantContent 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 SearchRelevantContent. 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.
SearchRelevantContent 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.