# NHTSA Vehicle Recalls Scraper (`neuton/nhtsa-vehicle-recalls-scraper`) Actor Search official NHTSA recall records by vehicle make, model, year, or campaign number. Export recall summaries, components, remedies, dates, and campaign IDs for automotive safety monitoring. - **URL**: https://apify.com/neuton/nhtsa-vehicle-recalls-scraper.md - **Developed by:** [Ashwin Prasad](https://apify.com/neuton) (community) - **Categories:** Business, AI, Automation - **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/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 ## NHTSA Vehicle Recalls Scraper Search official National Highway Traffic Safety Administration recall data for vehicle safety monitoring, automotive compliance, dealership research, used-car due diligence, and parts/remedy analysis. This actor is useful for dealers, fleets, insurance teams, marketplaces, automotive researchers, and compliance workflows that need official recall intelligence by make, model, year, or campaign number. ### What it returns - NHTSA campaign number and manufacturer - Component, report received date, summary, consequence, remedy, and notes - Input vehicle make/model/year context - NHTSA recall search URL and raw official record Use it to monitor recalls for fleets, compare vehicle risk, enrich VIN-adjacent workflows, or build recall intelligence datasets without running a browser. ### Common use cases - Monitor vehicle recalls for fleets, dealerships, repair networks, and used-car marketplaces - Enrich automotive listings with recall risk context - Research manufacturer, component, consequence, and remedy patterns - Build compliance, insurance, resale, and safety dashboards from official NHTSA data - Feed recall rows into spreadsheets, BI tools, CRM records, and AI agents ### Agent and automation workflows Use this actor as an official NHTSA recall data source for dealership monitors, fleet safety checks, used-car marketplace enrichment, insurance workflows, and AI agents. Scheduled tasks can watch makes, models, years, or campaign numbers and send new recall rows to Google Sheets, Airtable, BI tools, webhooks, or internal compliance systems. ### SEO keywords NHTSA recalls scraper, vehicle recall data API, car recall scraper, automotive safety data, NHTSA campaign number lookup, vehicle recall monitor, used car recall data, dealership recall intelligence. ### Pricing recommendation Launch around $3 per 1,000 recall rows. Raise toward $5 per 1,000 rows after recurring fleet, dealership, insurance, or marketplace usage appears. ### Sample input ```json { "vehicles": [ { "make": "Tesla", "model": "Model 3", "modelYear": 2022 } ], "maxResultsPerSearch": 5 } ```` # Actor input Schema ## `vehicles` (type: `array`): Vehicle objects with make, model, and modelYear. ## `campaignNumbers` (type: `array`): Exact NHTSA campaign numbers such as 22V702000. ## `maxResultsPerSearch` (type: `integer`): Maximum rows per vehicle or campaign search. ## Actor input object example ```json { "vehicles": [ { "make": "Tesla", "model": "Model 3", "modelYear": 2022 } ], "maxResultsPerSearch": 100 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "vehicles": [ { "make": "Tesla", "model": "Model 3", "modelYear": 2022 } ] }; // Run the Actor and wait for it to finish const run = await client.actor("neuton/nhtsa-vehicle-recalls-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "vehicles": [{ "make": "Tesla", "model": "Model 3", "modelYear": 2022, }] } # Run the Actor and wait for it to finish run = client.actor("neuton/nhtsa-vehicle-recalls-scraper").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 '{ "vehicles": [ { "make": "Tesla", "model": "Model 3", "modelYear": 2022 } ] }' | apify call neuton/nhtsa-vehicle-recalls-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=neuton/nhtsa-vehicle-recalls-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "NHTSA Vehicle Recalls Scraper", "description": "Search official NHTSA recall records by vehicle make, model, year, or campaign number. Export recall summaries, components, remedies, dates, and campaign IDs for automotive safety monitoring.", "version": "1.0", "x-build-id": "YRb4PN8lLtpbyW27z" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/neuton~nhtsa-vehicle-recalls-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-neuton-nhtsa-vehicle-recalls-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/neuton~nhtsa-vehicle-recalls-scraper/runs": { "post": { "operationId": "runs-sync-neuton-nhtsa-vehicle-recalls-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/neuton~nhtsa-vehicle-recalls-scraper/run-sync": { "post": { "operationId": "run-sync-neuton-nhtsa-vehicle-recalls-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "vehicles": { "title": "Vehicles", "type": "array", "description": "Vehicle objects with make, model, and modelYear." }, "campaignNumbers": { "title": "Campaign numbers", "type": "array", "description": "Exact NHTSA campaign numbers such as 22V702000.", "items": { "type": "string" } }, "maxResultsPerSearch": { "title": "Max results per search", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum rows per vehicle or campaign search.", "default": 100 } } }, "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 } } } } } } } } } } ```