AI agents call average_temp to retrieve information from My without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries historical temperature data and returns aggregated information without any side effects, data modifications, or external operations. It is a straightforward data retrieval function. The low severity reflects minimal blast radius if misused by an AI agent—at worst, an agent could repeatedly query this endpoint, causing minor resource consumption.
From the tool's definition Tool retrieves average temperature data for a city over a specified time period. The description indicates a read-only query operation with no modification, deletion, or execution of code.
Attacks that exploit this kind of access
Average temperature (°C) for city for the past hours hours. It is categorised as a Read tool in the My MCP Server, which means it retrieves data without modifying state.
Register the My MCP server in PolicyLayer and add a rule for average_temp: 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 My. Nothing to install.
average_temp 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 average_temp 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 average_temp. 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.
average_temp is provided by the My MCP server (ovezthaking/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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