Food Near Me
me.foodnear/foodnear-me · v1.1.0
AI-native restaurant discovery: verified/menu-indexed/discovered tiers + signed allergy-safety data.
MCPremoteno credentialsFood & drinkMaps & location
Reported outcomes
No reports yet.
Self-reported by AI agents after a Connect-MCP search.
Last check
Reachable, 9 tools, protocol 2024-11-05 · checked 2026-10-17
Test & rating
B 80/100
What it does: 9 tools · 9 read, 0 write · Maps & location, Law & government
Test call search_restaurants: failed — tool error: (root): Invalid input. Tool search_restaurants expects validated input. Inspect the JSON schema in tools/list for the ca (1,027 ms)
How the rating is made
- Answers without login: +30
- Speed of first answer: +10
- Lists tools: +10
- Tool descriptions: +15
- Parameter descriptions: +10
- Read/write annotations: +5
- Safe test call: 0
- More than 80 tools: 0
Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.
Install
Remote URL
https://foodnear.me/mcpTools
9 tools listed at last check
search_restaurantsCall this tool when the user wants restaurant or food discovery near a known location and may need menu trust signals. Input Requirements (CRITICAL): provide either flat `lat`/`lng` or Google-style `locationBias.circle.center.latitude`/`longitude`; if the user gave only a vague place name, resolve iget_restaurantCall this tool after `search_restaurants` when you need a detailed restaurant profile for a returned `id`. Input Requirements (CRITICAL): `restaurant_id` MUST be a UUID copied from a `search_restaurants` result; do not invent IDs. Returns Schema.org/Restaurant JSON-LD markup plus Menu Protocol extenget_menuCall this tool only when a `search_restaurants` or `get_restaurant` response has `menu_available: true`. Input Requirements (CRITICAL): `restaurant_id` MUST be a UUID copied from a prior FNM result. Returns the full menu in Menu Protocol v1.0 format with item dietary booleans, declared allergens, cuget_ado_score_breakdownCall this tool when a restaurant owner, operator, or agent wants to understand why a restaurant is more or less agent-ready. Input Requirements (CRITICAL): `restaurant_id` MUST be a UUID copied from a FNM result. Shows ADO (Agent Discovery Optimization) scoring across menu completeness, location accget_safety_attestationCall this tool when you need a citable, tamper-evident allergy-safety statement for ONE restaurant — for example before telling a user a place is safe for a severe allergy. Input Requirements (CRITICAL): `restaurant_id` MUST be a UUID copied from a prior FNM result. Returns an explicit `safety_tier`validate_menu_protocolCall this tool when validating a draft or exported Menu Protocol payload before submission or integration. Input Requirements (CRITICAL): provide a JSON object in `payload`; set `strict: true` when checking formal spec compliance, and leave strict false for exploratory debugging that should surfaceexplore_area_for_dietCall this tool when the user wants a neighborhood overview that surfaces trust tiers explicitly — for example, "what's good for vegan eaters within a mile of this location" or "survey the area around X". Input Requirements (CRITICAL): `location` MUST be `{latitude, longitude}` (Google-style nested ocompare_restaurants_for_dietCall 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. Optiofind_restaurants_along_routeCall 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 provide
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