# FDA Food Recall Monitor & Watchlist Alerts (`frankycheese/fda-recall-match-delta`) Actor

Monitor official FDA food recalls against product, supplier, brand, classification, state, and distribution watchlists. Pay only for new matches or material source corrections, not every raw record.

- **URL**: https://apify.com/frankycheese/fda-recall-match-delta.md
- **Developed by:** [franklin mccheese](https://apify.com/frankycheese) (community)
- **Categories:** Automation, Business
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $200.00 / 1,000 new matched fda food recalls

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## FDA Recall Match Delta — Food Watchlists

Run daily or weekly. Pay only for newly seen FDA food-enforcement records that match your products, suppliers, brands, or distribution footprint.

### buyer wedge

Built for food distributors, private-label retailers, marketplace compliance teams, and food-safety consultants who need a narrow internal screening feed—not another bulk recall dump.

### why it is different

- **signal, not retrieval:** unmatched FDA records are omitted and free.
- **explainable matching:** every event lists the field, watch term, and deterministic match method.
- **correction-aware:** a materially changed source record emits `SOURCE_CORRECTION` once.
- **distribution matching:** state abbreviations, state names, and explicit channel phrases are normalized without substring guessing.
- **replay-safe:** stable event IDs and provider idempotency keys suppress duplicate charges.
- **bounded spend:** `maxEvents` and `maxTotalChargeUsd` cap each run before charging.
- **audit evidence:** every row includes the official API query, source fingerprint, timestamp, and disclaimer.

### source and scope

The Actor queries the official [openFDA food enforcement API](https://open.fda.gov/apis/food/enforcement/). No API key, browser, proxy, personal data, or AI inference is required. FDA states that enforcement data is generally updated weekly and is not maintained as an authoritative recall-lifecycle tracker. Accordingly, this Actor is an **internal screening aid** and emits new or corrected source records; it does not issue public alerts, provide medical/legal advice, or claim a recall was terminated or escalated.

### matching

At least one narrow watch term is required:

- `keywords`: phrase match across product description, recall reason, and code/lot information
- `firms`: normalized exact or phrase match against recalling firm
- `brands`: phrase match in product description
- `states`: exact firm-state or tokenized distribution-area match
- `distributionTerms`: phrase match in distribution text
- `classifications`: optional exact filter (`Class I`, `Class II`, `Class III`)

`baselineMode=emit_matches` returns matching records in the initial lookback window. Use `silent` to establish state without emitting or charging initial matches. Reuse the same `watchlistId`, settings, and `stateStoreName` for scheduled monitoring.

### output

Paid dataset rows are either:

- `NEW_MATCH` — `$0.20`
- `SOURCE_CORRECTION` — `$0.05`

Unmatched records, unchanged replays, silent baselines, malformed input, and failed source fetches are not paid events. A deterministic run report is stored as `REPORT` with source window, counts, receipts, state size, and claim scope.

### operational note

If openFDA returns an error or an unexpected response shape, the run fails before state is advanced or events are charged. Event settlement is fail-closed: an ambiguous prior settlement refuses another provider charge.

### quick start

Start with a silent baseline so historical matches do not create paid events, then schedule the identical input daily or weekly.

```json
{
  "watchlistId": "private-label-snacks",
  "brands": ["Example Brand"],
  "firms": ["Example Foods LLC"],
  "keywords": ["undeclared peanut"],
  "states": ["WA", "OR"],
  "classifications": ["Class I"],
  "lookbackDays": 14,
  "baselineMode": "silent",
  "maxEvents": 10,
  "maxTotalChargeUsd": 2,
  "stateStoreName": "private-label-snacks-fda"
}
```

After the baseline, keep `watchlistId`, watch terms, and `stateStoreName` stable. Route returned `NEW_MATCH` and `SOURCE_CORRECTION` rows to a compliance review queue. Confirm every action against the linked FDA source; this feed is deliberately not an emergency notification or recall-status system.

Useful workflow: Apify schedule → this actor → dataset webhook → Slack, email, ticket, or supplier-review queue. The event includes the matched field and term, so reviewers can see why it appeared without an AI explanation layer.

Other focused monitors: [local website-gap changes](https://apify.com/frankycheese/local-lead-delta), [Florida new entities](https://apify.com/frankycheese/new-entity-delta), and [Seattle pre-permit events](https://apify.com/frankycheese/municipal-pre-permit-intelligence).

# Actor input Schema

## `watchlistId` (type: `string`):

Stable 3-64 character ID for this watchlist.

## `keywords` (type: `array`):

Literal phrases matched against product, reason, and lot/code text.

## `firms` (type: `array`):

Normalized exact or phrase matches against the recalling firm.

## `brands` (type: `array`):

Literal phrases matched in the FDA product description.

## `states` (type: `array`):

Two-letter US abbreviations matched against firm state and distribution text.

## `distributionTerms` (type: `array`):

Phrases such as nationwide, online, or a channel name.

## `classifications` (type: `array`):

Optional exact filter. Examples: Class I, Class II, Class III.

## `lookbackDays` (type: `integer`):

Rolling report-date window. FDA says enforcement data is generally updated weekly.

## `baselineMode` (type: `string`):

Emit current matches for immediate value, or silently establish a baseline.

## `maxEvents` (type: `integer`):

Hard cap on paid signals delivered in one run.

## `maxTotalChargeUsd` (type: `number`):

Hard ceiling derived before any charge. New match $0.20; source correction $0.05.

## `maxSourceRecords` (type: `integer`):

Bound the official API response to at most 1,000 records.

## `stateStoreName` (type: `string`):

Reuse this name on scheduled runs for replay suppression.

## `resetState` (type: `boolean`):

Deliberately discard this watchlist configuration's baseline.

## Actor input object example

```json
{
  "watchlistId": "my-food-watchlist",
  "keywords": [
    "undeclared allergen"
  ],
  "firms": [],
  "brands": [],
  "states": [],
  "distributionTerms": [],
  "classifications": [],
  "lookbackDays": 14,
  "baselineMode": "emit_matches",
  "maxEvents": 100,
  "maxTotalChargeUsd": 20,
  "maxSourceRecords": 1000,
  "stateStoreName": "fda-recall-match-delta-state",
  "resetState": false
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `report` (type: `string`):

No description

# 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("frankycheese/fda-recall-match-delta").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("frankycheese/fda-recall-match-delta").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).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 frankycheese/fda-recall-match-delta --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,frankycheese/fda-recall-match-delta"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/ZQ9vs4f9pqyiHDvBg/builds/ffgYOe3u9dPKhEIb9/openapi.json