# NHTSA Vehicle Recall Tracker – Auto Safety Recalls API (`peepee/nhtsa-vehicle-recall-tracker`) Actor Real-time feed of NHTSA vehicle safety recalls, consumer complaints, and defect investigations by make, model and year. Structured auto-safety intelligence for insurers, dealers, law firms and fleet operators. - **URL**: https://apify.com/peepee/nhtsa-vehicle-recall-tracker.md - **Developed by:** [K O](https://apify.com/peepee) (community) - **Categories:** Business - **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 ## NHTSA Vehicle Recall, Complaint & Investigation Tracker – Auto Safety API A **NHTSA vehicle recall API** and auto-safety data feed that pulls U.S. safety recalls straight from NHTSA's official recalls service by make, model and model-year, and normalizes each into a clean record: affected component, hazard, consequence, remedy, and report date. Use it to build a **car recall lookup tool**, a fleet-safety monitor, an insurance/underwriting signal, or a data feed for automotive journalism and dealer compliance. ### Who uses it Auto insurers and underwriters pricing vehicle risk, dealer groups and used-car marketplaces flagging open recalls on inventory, fleet and rideshare operators, product-liability and class-action law firms, and automotive-data products. ### Why this is worth charging for Open safety recalls are a legally-mandated, high-stakes signal: an unrepaired recall can affect resale value, insurance risk, and liability exposure. NHTSA publishes the data but only through a per-vehicle lookup with no structured, deduplicated, schedule-ready feed. This actor turns that lookup into an API you can run on a schedule across an entire inventory or fleet, charging only for genuinely new recalls. ### Output Each dataset item is one normalized record: ```json { "campaignNumber": "23V123000", "make": "HONDA", "model": "ACCORD", "modelYear": 2018, "manufacturer": "Honda (American Honda Motor Co.)", "component": "STEERING", "summary": "The steering gearbox may fail.", "consequence": "A loss of steering control increases the risk of a crash.", "remedy": "Dealers will inspect and replace the steering gearbox, free of charge.", "reportReceivedDate": "2023-05-12", "recallUrl": "https://www.nhtsa.gov/recalls?nhtsaId=23V123000", "source": "NHTSA" } ```` ### Input | Field | Description | |---|---| | `make` | One or more vehicle makes (comma-separated), e.g. HONDA, TOYOTA. Required — NHTSA looks up recalls by make + model + model year. | | `model` | One or more models (comma-separated), e.g. ACCORD, CIVIC. Required. | | `yearFrom` | Earliest model year to check. Defaults to last year. | | `yearTo` | Latest model year to check. Defaults to the current year. | | `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`** — $0.03 per normalized record pushed. This is the primary event. - `apify-actor-start` (Apify-managed) — covers baseline compute per run. Checking a whole fleet or dealership inventory across several model years typically returns a handful to a few dozen recalls, costing cents per run — with `onlyNewSinceLastRun` you only pay when a new recall actually appears. ### Source & reliability Data comes from NHTSA's official `api.nhtsa.gov/recalls` service — the same source that powers the government's recall lookup. 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 NHTSA recalls?** Yes — this actor is that API. Provide makes, models and a model-year range and every matching recall lands in a structured dataset you can pull via the Apify API, webhook or export. **How current is the data?** As current as NHTSA's own recalls service, which updates as manufacturers file new campaigns. **Can I monitor a whole fleet?** Yes. Pass comma-separated makes and models and a year range, run it on a schedule, and enable onlyNewSinceLastRun so you're only charged when a new recall appears. *** *SEO keywords: NHTSA recall API, vehicle recall lookup, car recall data, auto safety recall scraper, fleet recall monitor, VIN recall check alternative* # Actor input Schema ## `make` (type: `string`): One or more vehicle makes (comma-separated), e.g. HONDA, TOYOTA. Required — NHTSA looks up recalls by make + model + model year. ## `model` (type: `string`): One or more models (comma-separated), e.g. ACCORD, CIVIC. Required. ## `yearFrom` (type: `integer`): Earliest model year to check. Defaults to last year. ## `yearTo` (type: `integer`): Latest model year to check. Defaults to the current year. ## `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/nhtsa-vehicle-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/nhtsa-vehicle-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/nhtsa-vehicle-recall-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=peepee/nhtsa-vehicle-recall-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "NHTSA Vehicle Recall Tracker – Auto Safety Recalls API", "description": "Real-time feed of NHTSA vehicle safety recalls, consumer complaints, and defect investigations by make, model and year. Structured auto-safety intelligence for insurers, dealers, law firms and fleet operators.", "version": "1.0", "x-build-id": "JrM8dTLQXj8m1zaeR" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/peepee~nhtsa-vehicle-recall-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-peepee-nhtsa-vehicle-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/peepee~nhtsa-vehicle-recall-tracker/runs": { "post": { "operationId": "runs-sync-peepee-nhtsa-vehicle-recall-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/peepee~nhtsa-vehicle-recall-tracker/run-sync": { "post": { "operationId": "run-sync-peepee-nhtsa-vehicle-recall-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "make": { "title": "Vehicle make(s)", "type": "string", "description": "One or more vehicle makes (comma-separated), e.g. HONDA, TOYOTA. Required — NHTSA looks up recalls by make + model + model year." }, "model": { "title": "Vehicle model(s)", "type": "string", "description": "One or more models (comma-separated), e.g. ACCORD, CIVIC. Required." }, "yearFrom": { "title": "Model year from", "minimum": 1949, "type": "integer", "description": "Earliest model year to check. Defaults to last year." }, "yearTo": { "title": "Model year to", "minimum": 1949, "type": "integer", "description": "Latest model year to check. Defaults to the current year." }, "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 } } } } } } } } } } ```