Call this tool when the user wants route-adjacent dining options between two known coordinates and may care about dietary fit. Input Requirements (CRITICAL): both origin and destination MUST be {latitude, longitude} objects; optional route_polyline MUST be a valid encoded polyline if provided. Th...
Risk signalsAccepts file system path (destination)
Part of the Food Near Me server.
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AI agents call find_restaurants_along_route 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 find_restaurants_along_route 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": {
"find_restaurants_along_route": {}
}
}See the full Food Near Me policy for all 8 tools.
These attack patterns abuse exactly the kind of access find_restaurants_along_route 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 route-adjacent dining options between two known coordinates and may care about dietary fit. Input Requirements (CRITICAL): both origin and destination MUST be {latitude, longitude} objects; optional route_polyline MUST be a valid encoded polyline if provided. The tool samples waypoints along the corridor, merges nearby search matches, then ranks by dietary match count (when requested), trust tier, and route proximity. SHOULD provide route_polyline from your routing source for tighter ranking; otherwise fallback is a local great-circle approximation. MUST check menu_available before calling get_menu on returned ids. Non-verified places entries include a structured claim_invitation the agent SHOULD surface 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 find_restaurants_along_route: 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.
find_restaurants_along_route 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_restaurants_along_route 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_restaurants_along_route. 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_restaurants_along_route 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.
Free to start. No card required.
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