AI agents call central_get_alerts to retrieve information from Central without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
The tool retrieves alert data from a network management system. While the description is empty, the naming convention ('get_alerts'), server context (query/retrieval focus), and sibling tools all indicate this is a read operation with no side effects.
From the tool's definition Tool name 'central_get_alerts' and server description stating it 'query[s] HPE Aruba Networking Central data... (alerts, events)' indicates retrieval of alert information.
Attacks that exploit this kind of access
central_get_alerts. It is categorised as a Read tool in the Central MCP Server, which means it retrieves data without modifying state.
Register the Central MCP server in PolicyLayer and add a rule for central_get_alerts: 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 Central. Nothing to install.
central_get_alerts 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 central_get_alerts 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 central_get_alerts. 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.
central_get_alerts is provided by the Central MCP server (karthikskumar98/central-mcp-server). 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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