get_execution_plan
AI agents call get_execution_plan to retrieve information from AWS IoT SiteWise 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 strongly indicates a retrieval/query operation ('get_') rather than modification or execution. In AWS IoT SiteWise context, an execution plan would be a data artifact to fetch for review. Without a description, confidence is moderate, but the naming convention and sibling tool patterns support Read classification.
From the tool's definition Tool name 'get_execution_plan' suggests retrieving a pre-computed plan or schedule. Sibling tools include primarily Read operations (aggregate, analyze_*) and administrative Write operations. No description provided to confirm, which lowers confidence.
Attacks that exploit this kind of access
get_execution_plan. It is categorised as a Read tool in the AWS IoT SiteWise MCP Server MCP Server, which means it retrieves data without modifying state.
Register the AWS IoT SiteWise MCP Server MCP server in PolicyLayer and add a rule for get_execution_plan: 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 IoT SiteWise MCP Server. Nothing to install.
get_execution_plan 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_execution_plan 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_execution_plan. 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_execution_plan is provided by the AWS IoT SiteWise MCP Server MCP server (awslabs.aws-iot-sitewise-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.