# US Restaurant Health Inspection Scores (`filingradar/us-restaurant-inspections`) Actor

Restaurant & food-establishment health inspections from public city open-data (NYC + Chicago), normalized to one schema with result, letter grade, score, critical flags, and geocode. One row per inspection. Public data only.

- **URL**: https://apify.com/filingradar/us-restaurant-inspections.md
- **Developed by:** [Filing Radar](https://apify.com/filingradar) (community)
- **Categories:** Business, Lead generation
- **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$4.00 / 1,000 results

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## US Restaurant Health Inspection Scores

**Every restaurant inspection, normalized to one schema.** This Actor pulls **health-inspection results** from official city open-data portals — with **result, letter grade, score, critical-violation flags, and geocode** — one clean row per inspection, across cities that each report it differently. Flags the **recent ones** (last 30 days).

> **Live coverage: New York City + Chicago.** More cities on request. 100% public government data — no logins, no gray areas.

***

### Who uses this

- **Food-delivery & reservation platforms** — surface or screen on safety; flag failing venues.
- **Restaurant & hospitality insurers, underwriters** — risk-score a venue before binding.
- **Franchise & multi-unit QA** — monitor every location's inspections in one feed.
- **Food-safety SaaS, proptech, market researchers** — a normalized cross-city score nobody else publishes.
- **Real estate** — failing/closing restaurants signal turnover.

### What's in every record (one row per inspection)

| Field | Example |
|-------|---------|
| `name` / `cuisine_or_type` | `Mona Lisa Pizzeria & Ristorante` / `Pizza` |
| `result` | `pass` · `conditional` · `fail` · `closed` |
| `grade` / `score` | `A`/`B`/`C` (NYC) · `22` |
| `critical_flag` | `true` |
| `violation_summary` | `Evidence of mice in establishment's food areas` |
| `inspection_date` / `inspection_type` | `2026-06-15` / `Cycle Inspection` |
| `risk` | `Risk 1 (High)` (Chicago) |
| `address` · `city` · `county` · `state` · `zip` | `839 Annadale Rd`, `Staten Island`, `NY` |
| `lat` / `lng` | geocoded where the city provides it |
| `change_type` | **`NEW`** = inspected in the last 30 days |

Export to **JSON, CSV, or Excel**, or pull via the **Apify API** into your app.

### Inputs

| Input | What it does |
|-------|--------------|
| **Cities / states** | `NY` (NYC), `IL` (Chicago). |
| **Filter** | Empty = all. `["NEW"]` = only inspections in the last 30 days. |
| **Max records per city** | Cap the volume (and your cost) per run. |

### Pricing

**Pay per result** — you only pay for the records you receive: **$0.004 per delivered inspection record.** No subscription, no minimums.

### Data sources & legality

100% **public** city open-data APIs, intended for reuse:

- **NYC** — DOHMH Restaurant Inspection Results (`data.cityofnewyork.us`)
- **Chicago** — Food Inspections (`data.cityofchicago.org`)

Public establishment-level inspection records — no personal data. The Actor only touches public endpoints, never logged-in or ToS-gated sources, and rate-limits politely.

### FAQ

**How fresh is it?** As fresh as the city portals — `NEW` flags any inspection within the last 30 days.

**Which cities?** NYC + Chicago now. Want LA, Austin, Seattle, or your city next? Request it.

**Is this AI-generated?** The data is real government open-data; an automated pipeline normalizes and de-duplicates it. No fabricated rows, ever.

**One row per inspection?** Yes — NYC reports one row per violation; we collapse to one row per inspection with the grade/score/result.

***

<sub>**For developers / source:** zero-dependency Node 20 (built-in `fetch`). `node src/run.mjs` runs the pipeline locally. Public-data only; normalization is deterministic.</sub>

# Actor input Schema

## `cities` (type: `array`):

Which to include. Supported: NY (New York City), IL (Chicago). More on request.

## `change_types` (type: `array`):

Empty = all inspections. \["NEW"] = only inspections in the last 30 days.

## `limit` (type: `integer`):

Upper bound on rows pulled per city per run.

## Actor input object example

```json
{
  "cities": [
    "NY",
    "IL"
  ],
  "change_types": [],
  "limit": 1000
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("filingradar/us-restaurant-inspections").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("filingradar/us-restaurant-inspections").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call filingradar/us-restaurant-inspections --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=filingradar/us-restaurant-inspections",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/8PcP8dQ8bMtLWLG5L/builds/XfZqpXt3ghnGavmTQ/openapi.json