Read SageMaker pipeline execution status for a started notebook job.
AI agents call get_sagemaker_job_status to retrieve information from AWS Notebook Runner MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries the state of an existing SageMaker job execution. It performs a pure read operation that retrieves data about a job's progress and status. No data is created, modified, deleted, or executed. The blast radius is minimal—worst case, an agent learns the status of a job it already started, which is informational only. The 'Read' category is appropriate.
From the tool's definition Tool name contains 'get_' and description states 'Read SageMaker pipeline execution status' — retrieves status information without modification or side effects.
Attacks that exploit this kind of access
Read SageMaker pipeline execution status for a started notebook job. It is categorised as a Read tool in the AWS Notebook Runner MCP MCP Server, which means it retrieves data without modifying state.
Register the AWS Notebook Runner MCP server in PolicyLayer and add a rule for get_sagemaker_job_status: 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 AWS Notebook Runner MCP. Nothing to install.
get_sagemaker_job_status 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_sagemaker_job_status 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_sagemaker_job_status. 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_sagemaker_job_status is provided by the AWS Notebook Runner MCP server (yummytastycode/aws-notebook-runner-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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