AI agents call get_houses to retrieve information from Baselings without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves information about the user's houses and their occupants. It performs no side effects, makes no modifications to data, executes no external code, and does not involve financial transactions. It is purely informational and falls squarely into the Read category with low severity.
From the tool's definition Tool name 'get_houses' and description 'List your houses and who lives in them' indicate a read-only query operation that retrieves and displays existing data without modification.
Attacks that exploit this kind of access
List your houses and who lives in them. It is categorised as a Read tool in the Baselings MCP Server, which means it retrieves data without modifying state.
Register the Baselings MCP server in PolicyLayer and add a rule for get_houses: 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 Baselings. Nothing to install.
get_houses 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_houses 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_houses. 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_houses is provided by the Baselings MCP server (jimbo530/baselings-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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