get_pricing_service_codes
AI agents call get_pricing_service_codes 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 appears to fetch or retrieve pricing service codes, which is a read-only data retrieval operation. No side effects, modifications, deletions, or financial transactions are indicated. Empty description lowers confidence slightly, but the name clearly suggests lookup/fetch semantics rather than write, execute, or destructive operations.
From the tool's definition Tool name 'get_pricing_service_codes' indicates retrieval of pricing service code information. The description is empty, but the naming pattern strongly suggests a query/fetch operation that retrieves reference data without modification.
Attacks that exploit this kind of access
get_pricing_service_codes. 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_pricing_service_codes: 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_pricing_service_codes 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_pricing_service_codes 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_pricing_service_codes. 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_pricing_service_codes 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.