Get a list of connected clients to the Valkey server.
AI agents call client_list 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 connection metadata from a Valkey (Redis-compatible) server. It performs a read-only query that returns a list of currently connected clients. There are no side effects, no data modifications, no code execution, and no destructive or financial implications. The blast radius of misuse is minimal—an attacker could only discover which clients are connected, which is informational in nature.
From the tool's definition Tool name 'client_list' and description 'Get a list of connected clients to the Valkey server' indicate a query operation that retrieves information without modifying state or triggering external operations.
Attacks that exploit this kind of access
Get a list of connected clients to the Valkey server. 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 client_list: 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.
client_list 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 client_list 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 client_list. 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.
client_list 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.