Obtém os limiares de pressão configurados para as decisões de auto-scaling.
AI agents call limiares_scaling to retrieve information from MCP Officegest without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The verb 'Obtém' means 'Gets/Retrieves' in Portuguese, indicating this tool reads/fetches configured pressure thresholds for auto-scaling decisions. It has no side effects — it only returns configuration data. Low severity as it only exposes configuration settings.
From the tool's definition Obtém os limiares de pressão configurados para as decisões de auto-scaling
Attacks that exploit this kind of access
Obtém os limiares de pressão configurados para as decisões de auto-scaling. It is categorised as a Read tool in the MCP Officegest MCP Server, which means it retrieves data without modifying state.
Register the MCP Officegest MCP server in PolicyLayer and add a rule for limiares_scaling: 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 MCP Officegest. Nothing to install.
limiares_scaling 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 limiares_scaling 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 limiares_scaling. 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.
limiares_scaling is provided by the MCP Officegest MCP server (rubencodex86/officegest-api-v2-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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