Find variables matching a wildcard pattern.
AI agents call find_variables to retrieve information from ACM MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool searches for and retrieves variables based on a pattern match. It retrieves information about existing variables without creating, modifying, deleting, or executing operations. It is a read-only query function with minimal blast radius if misused by an AI agent.
From the tool's definition Tool name 'find_variables' and description 'Find variables matching a wildcard pattern' indicate a query/search operation with no side effects.
Attacks that exploit this kind of access
Find variables matching a wildcard pattern. It is categorised as a Read tool in the ACM MCP Server MCP Server, which means it retrieves data without modifying state.
Register the ACM MCP Server MCP server in PolicyLayer and add a rule for find_variables: 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 ACM MCP Server. Nothing to install.
find_variables 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 find_variables 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 find_variables. 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.
find_variables is provided by the ACM MCP Server MCP server (pekosann/acm-mcp). 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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