Read specific DSQL documentation pages
AI agents call dsql_read_documentation 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 performs a straightforward retrieval of documentation text. Reading documentation has no side effects, does not execute code or queries, does not modify data, and poses no destructive or financial risk. The confidence is high because the intent is unambiguous from both name and description.
From the tool's definition Tool name 'dsql_read_documentation' combined with description 'Read specific DSQL documentation pages' explicitly indicates a read-only operation that retrieves documentation content without modifying or executing anything.
Attacks that exploit this kind of access
Read specific DSQL documentation pages. 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 dsql_read_documentation: 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.
dsql_read_documentation 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 dsql_read_documentation 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 dsql_read_documentation. 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.
dsql_read_documentation 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.