获取 Live2D 桌面宠物的所有当前设置：窗口大小、位置、透明度、模型缩放、偏移等。
AI agents call settings_get to retrieve information from Live2d To Agent without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and retrieves existing settings (window size, position, transparency, model scale, offset, etc.) with no side effects, modifications, or state changes. It is a pure read operation on configuration parameters of a desktop pet application.
From the tool's definition Tool name 'settings_get' and description '获取 Live2D 桌面宠物的所有当前设置' (get all current settings of Live2D desktop pet) indicate retrieval of configuration data without modification.
Attacks that exploit this kind of access
获取 Live2D 桌面宠物的所有当前设置：窗口大小、位置、透明度、模型缩放、偏移等。. It is categorised as a Read tool in the Live2d To Agent MCP Server, which means it retrieves data without modifying state.
Register the Live2d To Agent MCP server in PolicyLayer and add a rule for settings_get: 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 Live2d To Agent. Nothing to install.
settings_get 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 settings_get 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 settings_get. 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.
settings_get is provided by the Live2d To Agent MCP server (lmy414/live2d-to-agent). 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.
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