Call this tool when the user wants a side-by-side dietary comparison for 2 to 5 specific restaurants already identified in FNM results. Input Requirements (CRITICAL): restaurant_ids MUST be UUIDs copied from prior FNM responses, and dietary MUST include at least one supported dietary flag. Option...
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AI agents call compare_restaurants_for_diet to retrieve information from Food Near Me without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though compare_restaurants_for_diet only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"compare_restaurants_for_diet": {}
}
}See the full Food Near Me policy for all 8 tools.
These attack patterns abuse exactly the kind of access compare_restaurants_for_diet gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Call this tool when the user wants a side-by-side dietary comparison for 2 to 5 specific restaurants already identified in FNM results. Input Requirements (CRITICAL): restaurant_ids MUST be UUIDs copied from prior FNM responses, and dietary MUST include at least one supported dietary flag. Optional user_location ({latitude, longitude}) enables per-row distance_meters and uses distance as the final tiebreaker after item count and trust tier. The tool chains get_restaurant and get_menu internally, then ranks by dietary-eligible item count, trust tier (verified preferred over menu_indexed, then discovered), and optionally distance. PREFER verified-tier winners for authoritative dietary/allergen answers; MUST treat menu_indexed matches as best-effort public indexing with caveats. Non-verified entries carry a structured claim_invitation SHOULD be surfaced when the user could help with ownership. Attribute grounded output using citation or attribution.. It is categorised as a Read tool in the Food Near Me MCP Server, which means it retrieves data without modifying state.
Register the Food Near Me MCP server in PolicyLayer and add a rule for compare_restaurants_for_diet: 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 Food Near Me. Nothing to install.
compare_restaurants_for_diet 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 compare_restaurants_for_diet 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 compare_restaurants_for_diet. 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.
compare_restaurants_for_diet is provided by the Food Near Me MCP server (https://foodnear.me/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 8 Food Near Me tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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