AI agents call get_meal_suggestions to retrieve information from Rohlik without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
meal_type | string | Yes | Type of meal or occasion (enum): breakfast, lunch, dinner, snack, baking, drinks, or healthy |
items_count | number | — | Number of items to suggest (3-30, default: 10) |
prefer_frequent | boolean | — | Prefer items you order frequently (default: true) |
orders_to_analyze | number | — | Number of recent orders to analyze (1-20, default: 5) |
Parameters from the server's own tool schema.
This tool retrieves personalized meal suggestions based on purchase history. It queries data and returns recommendations without creating, modifying, deleting, or executing any operations. The blast radius of misuse is minimal—an attacker could only receive unwanted suggestions, not modify cart, orders, or financial data.
From the tool's definition Tool name 'get_meal_suggestions' and description 'Get smart shopping suggestions' indicate data retrieval only. The verb 'Get' and phrase 'suggestions' confirm read-only operation with no modifications or side effects.
Attacks that exploit this kind of access
Get smart shopping suggestions for specific meal types (breakfast, lunch, dinner, etc.) based on your purchase history. It is categorised as a Read tool in the Rohlik MCP Server, which means it retrieves data without modifying state.
get_meal_suggestions accepts 4 parameters: meal_type, items_count, prefer_frequent, orders_to_analyze. Required: meal_type. The full parameter table on this page comes from the server's own tool schema.
Register the Rohlik MCP server in PolicyLayer and add a rule for get_meal_suggestions: 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 Rohlik. Nothing to install.
get_meal_suggestions 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_meal_suggestions 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_meal_suggestions. 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_meal_suggestions is provided by the Rohlik MCP server (@tomaspavlin/rohlik-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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