# CPSC Consumer Product Recall Tracker – Product Safety API (`peepee/cpsc-product-recall-tracker`) Actor Structured feed of new U.S. Consumer Product Safety Commission (CPSC) recalls: product, hazard, remedy, units affected, and manufacturer. For retailers, marketplaces, compliance teams and product-liability lawyers. - **URL**: https://apify.com/peepee/cpsc-product-recall-tracker.md - **Developed by:** [K O](https://apify.com/peepee) (community) - **Categories:** Business, News - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## CPSC Consumer Product Recall Tracker – Product Safety API A **CPSC recall API** and product-safety data feed that pulls consumer-product recalls from the Consumer Product Safety Commission's official SaferProducts service and normalizes each into a clean record: product and model, hazard, remedy, units affected, manufacturer, importer and country of origin. Use it to build a **product recall monitor** for a retail catalog or marketplace, a compliance alerting tool, or a data feed for product-liability research. ### Who uses it Retailers and e-commerce marketplaces screening catalogs for recalled SKUs, compliance and product-safety teams, insurers, product-liability and consumer-protection law firms, and safety-focused consumer apps. ### Why this is worth charging for A recalled product still listed for sale is a direct legal and reputational liability. CPSC publishes recalls but only via a raw REST endpoint with deeply nested arrays and no deduplication or schedule-ready delivery. This actor turns it into a monitored feed keyed to your catalog, charging only for new recalls. ### Output Each dataset item is one normalized record: ```json { "recallId": 12345, "recallNumber": "24-123", "recallDate": "2024-03-01", "title": "Widget Space Heaters Recalled Due to Fire Hazard", "products": [ { "name": "Widget Heater", "model": "WH-100", "type": "Space heater", "units": 50000 } ], "totalUnits": 50000, "hazards": [ "Fire", "Burn" ], "remedies": [ "Refund" ], "manufacturers": [ "Widget Co" ], "manufacturerCountries": [ "China" ], "soldAt": "Online at example.com", "url": "https://www.cpsc.gov/Recalls/2024/example", "source": "CPSC SaferProducts" } ```` ### Input | Field | Description | |---|---| | `recallDateStart` | Only include recalls on or after this date. | | `recallDateEnd` | Only include recalls on or before this date. | | `recallTitle` | Filter recalls whose title contains this keyword (e.g. a product category or brand). | | `onlyNewSinceLastRun` | Recommended for schedules — skips records already returned by a previous run using persisted state, so you're only charged for genuinely new items. | | `maxItems` | Stop after this many normalized records. | ### Pricing (Pay-Per-Event) - **`query`** — $0.02, charged once per run for the API query/poll. - **`recall-record`** — $0.04 per normalized record pushed. This is the primary event. - `apify-actor-start` (Apify-managed) — covers baseline compute per run. A daily poll of new recalls returns a few records at most, costing pennies per run. Backfilling a full year of recalls is a one-time larger pull you control with the date range. ### Source & reliability Data comes from CPSC's official `saferproducts.gov` REST service. No proxies or anti-bot handling required. Run `npm test` for the offline self-test covering the normalizer, including edge cases and missing-field handling. ### FAQ **Is there an API for CPSC recalls?** Yes — this actor wraps CPSC's SaferProducts service and returns clean, deduplicated recall records you can pull via the Apify API, webhook or export. **Can I match recalls to my product catalog?** Yes. Filter by title keyword or date, then match the normalized product name/model and manufacturer fields against your SKUs downstream. **How far back does it go?** Set recallDateStart to backfill historical recalls; leave it blank and schedule the run to only capture new ones. *** *SEO keywords: CPSC recall API, consumer product recall data, product safety scraper, recalled products monitor, SaferProducts API, retail compliance recall feed* # Actor input Schema ## `recallDateStart` (type: `string`): Only include recalls on or after this date. ## `recallDateEnd` (type: `string`): Only include recalls on or before this date. ## `recallTitle` (type: `string`): Filter recalls whose title contains this keyword (e.g. a product category or brand). ## `maxItems` (type: `integer`): Stop after this many normalized records have been pushed. Leave blank for no limit (bounded by pagination settings). ## `onlyNewSinceLastRun` (type: `boolean`): Recommended for scheduled runs. Uses persisted state to skip records already returned earlier, so a recurring schedule only charges for genuinely new items. ## Actor input object example ```json { "onlyNewSinceLastRun": true } ``` # 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("peepee/cpsc-product-recall-tracker").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("peepee/cpsc-product-recall-tracker").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 peepee/cpsc-product-recall-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=peepee/cpsc-product-recall-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "CPSC Consumer Product Recall Tracker – Product Safety API", "description": "Structured feed of new U.S. Consumer Product Safety Commission (CPSC) recalls: product, hazard, remedy, units affected, and manufacturer. For retailers, marketplaces, compliance teams and product-liability lawyers.", "version": "1.0", "x-build-id": "RQBLaQVvsgdPKr4M8" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/peepee~cpsc-product-recall-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-peepee-cpsc-product-recall-tracker", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/peepee~cpsc-product-recall-tracker/runs": { "post": { "operationId": "runs-sync-peepee-cpsc-product-recall-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/peepee~cpsc-product-recall-tracker/run-sync": { "post": { "operationId": "run-sync-peepee-cpsc-product-recall-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "recallDateStart": { "title": "Recall date start (YYYY-MM-DD)", "type": "string", "description": "Only include recalls on or after this date." }, "recallDateEnd": { "title": "Recall date end (YYYY-MM-DD)", "type": "string", "description": "Only include recalls on or before this date." }, "recallTitle": { "title": "Title keyword", "type": "string", "description": "Filter recalls whose title contains this keyword (e.g. a product category or brand)." }, "maxItems": { "title": "Maximum records to return", "minimum": 1, "type": "integer", "description": "Stop after this many normalized records have been pushed. Leave blank for no limit (bounded by pagination settings)." }, "onlyNewSinceLastRun": { "title": "Only return records not seen in a previous run", "type": "boolean", "description": "Recommended for scheduled runs. Uses persisted state to skip records already returned earlier, so a recurring schedule only charges for genuinely new items.", "default": true } } }, "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 } } } } } } } } } } ```