# FDA Recall Monitor (`carranza-tech/fda-recall-monitor`) Actor Normalized FDA recall/enforcement records across food, drug & device categories from the openFDA API. Filter by category, date, classification, recipient state, and keyword. One unified schema. - **URL**: https://apify.com/carranza-tech/fda-recall-monitor.md - **Developed by:** [Alfredo Carranza](https://apify.com/carranza-tech) (community) - **Categories:** News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $3.00 / 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use 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 ## FDA Recall Monitor Normalized **FDA recall & enforcement records** across **food, drug, and device** categories, pulled from the official [openFDA](https://open.fda.gov) API. Built for compliance teams, legal/regulatory staff, food-safety professionals, retailers, and insurers who need to monitor recalls without watching the FDA site by hand. ### What you get One clean, normalized record per recall: | Field | Description | |-------|-------------| | `category` | `food`, `drug`, or `device` | | `recalling_firm` | Company issuing the recall | | `classification` | Class I / II / III (severity) | | `status` | Ongoing, Completed, Terminated | | `reason_for_recall` | Why the product was recalled | | `product_description` | Product affected | | `report_date` | Date FDA reported (normalized `YYYY-MM-DD`) | | `recall_initiation_date` | Date recall began | | `city` / `state` / `country` | Firm location | | `distribution_pattern` | Where the product was distributed | | `source_url` | FDA recalls reference | ### Filters (input) - **categories** — subset of `["food","drug","device"]` (default all three) - **since / until** — `report_date` range (`YYYY-MM-DD`) - **classification** — `Class I` / `Class II` / `Class III` - **state** — filter by firm state - **keyword** — substring match on reason + product description - **maxResultsPerCategory** — cap per category ### Example input ```json { "categories": ["food", "drug"], "classification": "Class I", "since": "2026-01-01", "maxResultsPerCategory": 500 } ```` ### Data source & notes - 100% official public data from the **openFDA** enforcement API — no scraping, no login. - `Class I` = most serious (reasonable probability of serious health consequences). - Data is public record. ### Pricing Pay-per-result. You pay only for the normalized recall records delivered — no fee just to run. Ideal as a low-cost monitoring feed. # Actor input Schema ## `categories` (type: `array`): Which openFDA enforcement categories to pull recalls from. ## `since` (type: `string`): Only return recalls with a report\_date on or after this date. Leave empty for no lower bound. ## `until` (type: `string`): Only return recalls with a report\_date on or before this date. Leave empty for no upper bound. ## `classification` (type: `string`): Optional recall classification filter. Class I is most serious. ## `state` (type: `string`): Optional. Restrict to recalls whose recalling-firm state matches this 2-letter code (applied client-side). ## `keyword` (type: `string`): Case-insensitive substring match against reason\_for\_recall + product\_description (e.g. 'listeria', 'undeclared', 'contamination'). ## `maxResultsPerCategory` (type: `integer`): Cap on how many recalls to return per category. ## Actor input object example ```json { "categories": [ "food", "drug", "device" ], "since": "2026-01-01", "until": "2026-12-31", "state": "CA", "keyword": "listeria", "maxResultsPerCategory": 500 } ``` # 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 '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("carranza-tech/fda-recall-monitor").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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("carranza-tech/fda-recall-monitor").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 carranza-tech/fda-recall-monitor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=carranza-tech/fda-recall-monitor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "FDA Recall Monitor", "description": "Normalized FDA recall/enforcement records across food, drug & device categories from the openFDA API. Filter by category, date, classification, recipient state, and keyword. One unified schema.", "version": "0.1", "x-build-id": "i2HDAUPXy4dr5HN5i" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/carranza-tech~fda-recall-monitor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-carranza-tech-fda-recall-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/carranza-tech~fda-recall-monitor/runs": { "post": { "operationId": "runs-sync-carranza-tech-fda-recall-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/carranza-tech~fda-recall-monitor/run-sync": { "post": { "operationId": "run-sync-carranza-tech-fda-recall-monitor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "categories" ], "properties": { "categories": { "title": "Categories", "type": "array", "description": "Which openFDA enforcement categories to pull recalls from.", "items": { "type": "string", "enum": [ "food", "drug", "device" ], "enumTitles": [ "Food", "Drug", "Device" ] }, "default": [ "food", "drug", "device" ] }, "since": { "title": "Reported since (YYYY-MM-DD)", "type": "string", "description": "Only return recalls with a report_date on or after this date. Leave empty for no lower bound." }, "until": { "title": "Reported until (YYYY-MM-DD)", "type": "string", "description": "Only return recalls with a report_date on or before this date. Leave empty for no upper bound." }, "classification": { "title": "Classification", "enum": [ "Class I", "Class II", "Class III" ], "type": "string", "description": "Optional recall classification filter. Class I is most serious." }, "state": { "title": "Recalling firm state (2-letter)", "type": "string", "description": "Optional. Restrict to recalls whose recalling-firm state matches this 2-letter code (applied client-side)." }, "keyword": { "title": "Keyword", "type": "string", "description": "Case-insensitive substring match against reason_for_recall + product_description (e.g. 'listeria', 'undeclared', 'contamination')." }, "maxResultsPerCategory": { "title": "Max results per category", "minimum": 1, "maximum": 25000, "type": "integer", "description": "Cap on how many recalls to return per category.", "default": 500 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```