Get operating hours and contact info for a specific Aldi store.
AI agents call get_store_hours to retrieve information from Aldi MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns store metadata (hours, contact details) without creating, modifying, deleting, or executing any actions. It is a straightforward read operation with minimal security implications.
From the tool's definition Tool retrieves operating hours and contact information for stores—purely informational queries with no data modification, deletion, or execution of external operations.
Attacks that exploit this kind of access
Get operating hours and contact info for a specific Aldi store. It is categorised as a Read tool in the Aldi MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Aldi MCP Server MCP server in PolicyLayer and add a rule for get_store_hours: 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 Aldi MCP Server. Nothing to install.
get_store_hours 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_store_hours 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_store_hours. 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_store_hours is provided by the Aldi MCP Server MCP server (markswendsen-code/mcp-aldi). 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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