get_promql_label_values
AI agents call get_promql_label_values 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.
This tool retrieves or queries metric label values, which is a read-only operation with no side effects, data modification, or code execution capability. PromQL label value lookups are informational queries. Low severity because misuse would only expose existing metric metadata without enabling destructive or financial actions.
From the tool's definition Tool name 'get_promql_label_values' indicates retrieval of label values from a Prometheus Query Language (PromQL) query context; the 'get_' prefix and '_values' suffix suggest data retrieval without modification.
Attacks that exploit this kind of access
get_promql_label_values. 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 get_promql_label_values: 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.
get_promql_label_values 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 get_promql_label_values 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 get_promql_label_values. 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.
get_promql_label_values 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.