Comprehensive Model Context Protocol server for managing Home Assistant through AI assistants.
Nothing to run from here
Food Near Me is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
9
tools declared
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trust score
remote
at its publisher
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calls last 7d
What it does
AI-native restaurant discovery: verified/menu-indexed/discovered tiers + signed allergy-safety data.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user --transport http food-near-me-mcp https://foodnear.me/mcp
# 2 — ask your agent for something these tools do
# search_restaurants, get_restaurant, get_menu and 6 more
Food Near Me costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
FOAll 1 server
foodnear1 server
1 category
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. Nothing here runs on your machine and nothing runs on ours: this server answers at its publisher’s own address, and what you install is the connection straight to it.
Claude Codedeclared by this listing
This is a public server: it answers at its publisher’s own address and this marketplace is not in the path. Claude Code registers it in one command; --scope user makes it available in every project. The transport below is http, as the publisher's own manifest declares it.
claude mcp add --scope user --transport http food-near-me-mcp https://foodnear.me/mcpReconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it answers at its publisher’s own address: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it writes
One config entry pointing straight at the publisher’s own address — this marketplace is not in the path, and nothing from this listing executes on your machine.
What you approve
9 tools, with what each one reads, writes and reaches shown before you agree — the same list on every route above. Read the tool surface.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
Call 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 it before calling or include a specific city/region in textQuery/query. Returns verified venues f
No parameter schema on file.
Call 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 extensions including ADO score, verification status, menu availability, payment methods, and dietary cert
| Parameter | Type | Required | Notes |
|---|---|---|---|
| restaurant_id | string | yes | Restaurant UUID (from search_restaurants results) |
Call 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, customization options, preparation times, trust notice, and signature metadata. PREFER `verification_s
| Parameter | Type | Required | Notes |
|---|---|---|---|
| restaurant_id | string | yes | Restaurant UUID (from search_restaurants results) |
Call 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 accuracy, data freshness, protocol compliance, verification status, and media context. MUST treat sub-s
| Parameter | Type | Required | Notes |
|---|---|---|---|
| restaurant_id | string | yes | Restaurant UUID |
Call 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. For a CURATED tier (dedicated, strong_protocol, shared_verify) it includes an Ed25519 `attes
| Parameter | Type | Required | Notes |
|---|---|---|---|
| restaurant_id | string | yes | Restaurant UUID |
Call 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 surface warnings without rejecting usable drafts. Returns validation errors, schema warnings, Schema.org com
| Parameter | Type | Required | Notes |
|---|---|---|---|
| payload | object | yes | The Menu Protocol JSON payload to validate. Should include version, domain, restaurant, and menu objects. |
| strict | boolean | no | If true, schema warnings are promoted to errors and valid reflects strict spec compliance. Default: false (lenient mode). |
Call 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 object). Returns three tier buckets — verified, menu_indexed, discovered — each trimmed to `top
| Parameter | Type | Required | Notes |
|---|---|---|---|
| location | object | yes | Center of the area to explore (Google-style nested latitude/longitude). |
| dietary | array | no | Optional dietary filter applied with AND logic. Only narrows the verified tier; menu_indexed and discovered rows pass through unfiltered (matches search_restaurants semantics). |
| radius_meters | number | no | Default 1000 m (about 0.62 mi). Max 80467 m (50 miles). |
| top_n_per_tier | integer | no | Default 3, max 10. Each tier bucket is trimmed independently. |
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
| Parameter | Type | Required | Notes |
|---|---|---|---|
| restaurant_ids | array | yes | UUIDs copied from prior search_restaurants results. |
| dietary | array | yes | Dietary flags applied with AND logic at item level. |
| user_location | object | no | Optional caller location. When set, each compared restaurant carries distance_meters (great-circle from this point) and distance becomes the final tiebreaker after item_count and trust tier. Restaur |
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 dietar
| Parameter | Type | Required | Notes |
|---|---|---|---|
| origin | object | yes | Route start coordinates. |
| destination | object | yes | Route end coordinates. |
| dietary | array | no | Optional dietary filter. When set, route ranking prefers restaurants with more matching menu items. |
| max_results | integer | no | Default 5, max 20. |
| route_polyline | string | no | Optional encoded polyline from the caller's routing source (Google encoded polyline format). |
Free
$0 forever
- Every tool — any call limit is its publisher’s, not ours
- No card, and mcprush charges nothing for it
- Runs at its publisher’s own address — this marketplace is not in the path
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install Food Near Me or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
—
Alert at 80% · then the tool returns a normal MCP error
Used this month: —
—Grade not published
No rule-by-rule report on file for this release
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
This listing is an address its publisher runs, and you connect to it directly — this marketplace is not in the path. The scanner reads packages and public source, and an address is neither: the repository linked on this page is where this record was collected from, not a copy of what the address serves, so it is not graded in its place. So there is no grade — not a withheld one, an unmeasured one.
Release history
This is an address its publisher runs: which release it serves is theirs to choose, so there is nothing here to pin. The history below is for reading; the current release on file is 1.1.0.
1.1.0
undated
latestNo release note was published with this version.
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no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish Food Near Me can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
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Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.