Get the index of value in array at path.
AI agents call json_arrindex 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 metadata (an array index) from existing data without modifying, executing arbitrary code, deleting, or moving money. It is a pure read operation with no side effects. The low severity reflects minimal blast radius—an agent misusing it could only retrieve incorrect index values, which would likely cause logic errors in subsequent operations rather than direct damage.
From the tool's definition Tool name 'json_arrindex' and description 'Get the index of value in array at path' indicate a query/lookup operation that retrieves positional information from JSON data structures.
Attacks that exploit this kind of access
Get the index of value in array at path. 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 json_arrindex: 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.
json_arrindex 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 json_arrindex 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 json_arrindex. 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.
json_arrindex 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.