recommend_indexes_loggroup
AI agents call recommend_indexes_loggroup 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.
Based on the name alone, this appears to be a read-like analytical tool that examines log groups and recommends index configurations without modifying data. The empty description reduces confidence. The name pattern ('recommend_*') suggests a non-destructive advisory function. However, without explicit description confirming it has no side effects, confidence is moderate.
From the tool's definition Tool name 'recommend_indexes_loggroup' suggests analysis/recommendation of log group indexes; no description provided to confirm exact behavior.
Attacks that exploit this kind of access
recommend_indexes_loggroup. 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 recommend_indexes_loggroup: 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.
recommend_indexes_loggroup 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 recommend_indexes_loggroup 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 recommend_indexes_loggroup. 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.
recommend_indexes_loggroup 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.