list_browser_sessions
AI agents call list_browser_sessions 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.
The tool name contains 'list', which is a classic Read operation pattern that retrieves or queries data without side effects. Although the description is empty (reducing confidence slightly), the naming convention strongly indicates this lists existing browser sessions rather than creating, modifying, or deleting them. No evidence of destructive, financial, or code execution capabilities.
From the tool's definition Tool name 'list_browser_sessions' indicates a retrieval/listing operation with no description provided. The 'list' verb and absence of modification language suggest read-only data retrieval.
Attacks that exploit this kind of access
list_browser_sessions. 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 list_browser_sessions: 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.
list_browser_sessions 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 list_browser_sessions 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 list_browser_sessions. 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.
list_browser_sessions 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.