check_sandman_gemma_lms_status
Report LM Studio/LMS residency diagnostics for Sandman Gemma without loading or unloading models.
This record as markdown: /tools/mapi-agent-memory/check-sandman-gemma-lms-status.md
What check_sandman_gemma_lms_status does on Mapi Agent Memory
AI agents call check_sandman_gemma_lms_status to retrieve information from Mapi Agent Memory without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why check_sandman_gemma_lms_status is rated Low
This tool queries the status of model residency in LM Studio without triggering any state changes, loading operations, or external side effects. It is a diagnostic/monitoring function that retrieves information only, fitting the Read category definition of 'retrieves or queries data; no side effects'.
From the tool's definition Tool description states it 'Report[s] LM Studio/LMS residency diagnostics' and explicitly excludes loading or unloading models. The verb 'report' and 'diagnostics' indicate data retrieval with no side effects.
Attacks that exploit this kind of access
The rule that runs check_sandman_gemma_lms_status safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mapi Agent Memory, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For check_sandman_gemma_lms_status, this is the rule to start with:
check_sandman_gemma_lms_status is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mapi Agent Memory, apply this rule, and every check_sandman_gemma_lms_status call is checked against it from then on.
Questions about check_sandman_gemma_lms_status
Report LM Studio/LMS residency diagnostics for Sandman Gemma without loading or unloading models. It is categorised as a Read tool in the Mapi Agent Memory MCP Server, which means it retrieves data without modifying state.
Register the Mapi Agent Memory MCP server in PolicyLayer and add a rule for check_sandman_gemma_lms_status: 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 Mapi Agent Memory. Nothing to install.
check_sandman_gemma_lms_status 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 check_sandman_gemma_lms_status 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 check_sandman_gemma_lms_status. 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.
check_sandman_gemma_lms_status is provided by the Mapi Agent Memory MCP server (cabo0m/mapi-agent-memory). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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