# NHTSA Vehicle Intelligence (`prophed/nhtsa-vehicle-intelligence`) Actor Decode VINs and fetch vehicle recall records from public NHTSA APIs as normalized dataset rows. - **URL**: https://apify.com/prophed/nhtsa-vehicle-intelligence.md - **Developed by:** [Prophed Com](https://apify.com/prophed) (community) - **Categories:** Automation, Developer tools, 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 Intelligence Decode VINs and fetch vehicle recall records from public NHTSA APIs, then return normalized Apify dataset rows. This Actor is useful for automotive marketplaces, fleet operations, due-diligence workflows, data enrichment, lead scoring, and vehicle safety monitoring. ### Use cases - Decode VINs into make, model, year, body class, engine, fuel, and manufacturing details. - Pull NHTSA recalls for make/model/year combinations. - Batch vehicle safety enrichment into a repeatable Apify run. - Export vehicle intelligence to CSV, JSON, Excel, webhooks, or downstream systems. ### Input ```json { "vins": ["1HGCM82633A004352"], "recallQueries": [ { "make": "Honda", "model": "Accord", "modelYear": "2003" } ], "includeRaw": false, "maxItems": 1000 } ```` Both `vins` and `recallQueries` are optional, but at least one should be provided for useful output. ### Output VIN decode rows: ```json { "recordType": "vin-decode", "vin": "1HGCM82633A004352", "make": "HONDA", "model": "Accord", "modelYear": "2003", "bodyClass": "Coupe", "engineCylinders": "6", "fuelTypePrimary": "Gasoline" } ``` Recall rows: ```json { "recordType": "recall", "make": "HONDA", "model": "ACCORD", "modelYear": "2003", "campaignNumber": "19V182000", "component": "AIR BAGS", "summary": "..." } ``` If an upstream request fails, the Actor writes a structured error row and continues with the remaining VINs or recall queries. ### Notes This Actor uses public NHTSA endpoints and does not require an API key. It is a data enrichment tool, not a substitute for official safety checks or legal compliance processes. # Actor input Schema ## `vins` (type: `array`): Vehicle Identification Numbers to decode. ## `recallQueries` (type: `array`): Recall lookups by make, model, and modelYear. ## `includeRaw` (type: `boolean`): Attach selected raw API fields to each row. ## `maxItems` (type: `integer`): Hard cap for dataset rows. ## `timeoutSecs` (type: `integer`): Per-request timeout. ## Actor input object example ```json { "vins": [ "1HGCM82633A004352" ], "recallQueries": [ { "make": "Honda", "model": "Accord", "modelYear": "2003" } ], "includeRaw": false, "maxItems": 1000, "timeoutSecs": 30 } ``` # Actor output Schema ## `results` (type: `string`): No description ## `summary` (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 = { "vins": [ "1HGCM82633A004352" ], "recallQueries": [ { "make": "Honda", "model": "Accord", "modelYear": "2003" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("prophed/nhtsa-vehicle-intelligence").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 = { "vins": ["1HGCM82633A004352"], "recallQueries": [{ "make": "Honda", "model": "Accord", "modelYear": "2003", }], } # Run the Actor and wait for it to finish run = client.actor("prophed/nhtsa-vehicle-intelligence").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 '{ "vins": [ "1HGCM82633A004352" ], "recallQueries": [ { "make": "Honda", "model": "Accord", "modelYear": "2003" } ] }' | apify call prophed/nhtsa-vehicle-intelligence --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=prophed/nhtsa-vehicle-intelligence", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "NHTSA Vehicle Intelligence", "description": "Decode VINs and fetch vehicle recall records from public NHTSA APIs as normalized dataset rows.", "version": "0.1", "x-build-id": "iFdlMt0exctXz6j9r" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/prophed~nhtsa-vehicle-intelligence/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-prophed-nhtsa-vehicle-intelligence", "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/prophed~nhtsa-vehicle-intelligence/runs": { "post": { "operationId": "runs-sync-prophed-nhtsa-vehicle-intelligence", "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/prophed~nhtsa-vehicle-intelligence/run-sync": { "post": { "operationId": "run-sync-prophed-nhtsa-vehicle-intelligence", "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": { "vins": { "title": "VINs", "type": "array", "description": "Vehicle Identification Numbers to decode." }, "recallQueries": { "title": "Recall queries", "type": "array", "description": "Recall lookups by make, model, and modelYear." }, "includeRaw": { "title": "Include raw data", "type": "boolean", "description": "Attach selected raw API fields to each row.", "default": false }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 50000, "type": "integer", "description": "Hard cap for dataset rows.", "default": 1000 }, "timeoutSecs": { "title": "Request timeout seconds", "minimum": 5, "maximum": 120, "type": "integer", "description": "Per-request timeout.", "default": 30 } } }, "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 } } } } } } } } } } ```