Read the current target state, including config, AppSwitch, log sources, and LSPosed scope.
AI agents call read_target_state to retrieve information from Algorithmaide without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs query and retrieval operations only. It reads configuration and state information from an Android device under analysis without modifying, executing code, deleting data, or triggering external side effects. The explicit 'Read' verb in both name and description, combined with the passive inspection of existing state, places it firmly in the Read category with low severity.
From the tool's definition Tool name 'read_target_state' and description explicitly state 'Read the current target state' with retrieval of config, AppSwitch, log sources, and LSPosed scope—no modification, deletion, or execution indicated.
Documented attack patterns abuse exactly the kind of access read_target_state gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Algorithmaide, and nothing reaches the server without passing your rules. This is the rule we recommend for read_target_state:
{
"version": "1",
"default": "deny",
"tools": {
"read_target_state": {}
}
}read_target_state is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Read the current target state, including config, AppSwitch, log sources, and LSPosed scope. It is categorised as a Read tool in the Algorithmaide MCP Server, which means it retrieves data without modifying state.
Register the Algorithmaide MCP server in PolicyLayer and add a rule for read_target_state: 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 Algorithmaide. Nothing to install.
read_target_state 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 read_target_state 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 read_target_state. 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.
read_target_state is provided by the Algorithmaide MCP server (vwww-droid/algorithmaide-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Algorithmaide, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
23 Algorithmaide tools catalogued and risk-classified — across an index of 43,000+ MCP servers.