get_server_info
Identify the connected SiLA server (name, type, UUID, version, vendor, description), list its
This record as markdown: /tools/lab-instrument-mcps/get-server-info.md
What get_server_info does on Pypi:labmcp Alicat
AI agents call get_server_info to retrieve information from Pypi:labmcp Alicat without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why get_server_info is rated Low
Tool retrieves server metadata and configuration without modifying state or triggering operations.
From the tool's definition Identify the connected SiLA server, list its
Attacks that exploit this kind of access
The rule that runs get_server_info safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Pypi:labmcp Alicat, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For get_server_info, this is the rule to start with:
get_server_info 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 Pypi:labmcp Alicat, apply this rule, and every get_server_info call is checked against it from then on.
Questions about get_server_info
Identify the connected SiLA server (name, type, UUID, version, vendor, description), list its. It is categorised as a Read tool in the Pypi:labmcp Alicat MCP Server, which means it retrieves data without modifying state.
Register the Pypi:labmcp Alicat MCP server in PolicyLayer and add a rule for get_server_info: 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 Pypi:labmcp Alicat. Nothing to install.
get_server_info 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_server_info 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_server_info. 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_server_info is provided by the Pypi:labmcp Alicat MCP server (pypi:labmcp-alicat). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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