# NHTSA Vehicle Complaints Scraper (`automation-lab/nhtsa-vehicle-complaints-scraper`) Actor Extract official NHTSA vehicle safety complaints by make, model, and model year for defect monitoring and automotive analytics. - **URL**: https://apify.com/automation-lab/nhtsa-vehicle-complaints-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## 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 Complaints Scraper Extract public NHTSA vehicle safety complaints by make, model, and model year. Use this actor to monitor consumer defect complaints, crash/fire flags, injury/death counts, incident dates, complaint filing dates, components, summaries, VIN values when provided, and product metadata from the official National Highway Traffic Safety Administration complaints API. ### What does NHTSA Vehicle Complaints Scraper do? NHTSA Vehicle Complaints Scraper queries the public NHTSA complaints endpoint and saves normalized complaint records to an Apify dataset. It is built for repeat monitoring and bulk automotive analysis. Typical use cases include: - 🚗 Track complaint volume for a specific make/model/year. - 🧯 Find fire-related or crash-related consumer complaints. - 🛠️ Monitor components mentioned in defect reports. - 📈 Build time-series complaint datasets for risk models. - ✅ Export official-source complaint summaries for compliance workflows. ### Who is it for? #### Auto dealers Dealers can review complaint patterns before buying, pricing, or certifying used vehicles. #### Fleet and compliance teams Fleet teams can monitor safety complaints across makes and model years used in their fleet. #### Insurers Insurance analysts can enrich vehicle-risk models with public complaint signals. #### Warranty and repair analytics teams Warranty teams can compare complaint components against claim patterns. #### Used-car data providers Vehicle data products can add complaint counts and summaries to model-year intelligence. ### Why use this actor? The NHTSA API is public, but raw API responses are not always convenient for recurring data pipelines. This actor adds: - Clean Apify dataset output. - Multi-vehicle input support. - Normalized booleans, numbers, dates, and components. - PPE billing that scales with saved complaint rows. - Ready-to-use API, webhook, scheduling, and export integrations. ### Data source The actor uses the official public NHTSA complaints endpoint: `https://api.nhtsa.gov/complaints/complaintsByVehicle` Required source parameters are: - `make` - `model` - `modelYear` The actor does not require a login, API key, browser session, or proxy. ### What data can I extract? | Field | Description | | --- | --- | | `queryMake` | Make submitted in your input | | `queryModel` | Model submitted in your input | | `queryModelYear` | Model year submitted in your input | | `odiNumber` | NHTSA ODI complaint identifier | | `manufacturer` | Manufacturer provided by NHTSA | | `crash` | Whether crash was reported | | `fire` | Whether fire was reported | | `numberOfInjuries` | Injury count in the complaint | | `numberOfDeaths` | Death count in the complaint | | `dateOfIncident` | Incident date when available | | `dateComplaintFiled` | Complaint filing date when available | | `vin` | VIN or partial VIN if NHTSA provides it | | `components` | Parsed component list | | `componentText` | Original component text | | `summary` | Consumer complaint summary | | `products` | Nested product metadata | | `sourceUrl` | NHTSA API URL used for the query | | `scrapedAt` | Extraction timestamp | ### How much does it cost to scrape NHTSA vehicle complaints? This actor uses pay-per-event pricing. You pay a small start fee per run and a per-complaint fee for each saved dataset item. The default input is intentionally small enough for testing, while realistic monitoring jobs can request hundreds or thousands of complaints. Apify shows the exact price before you start a run. ### Input options The main input is `vehicles`, an array of vehicle combinations. Example: ```json { "vehicles": [ { "make": "Honda", "model": "Accord", "modelYear": 2020 }, { "make": "Ford", "model": "F-150", "modelYear": 2021 } ], "maxComplaintsPerVehicle": 150, "maxItems": 500, "sortBy": "dateComplaintFiledDesc", "includeProducts": true } ```` You can also use single-vehicle shortcut fields: ```json { "make": "Toyota", "model": "Camry", "modelYear": 2022, "maxComplaintsPerVehicle": 100 } ``` ### Output example ```json { "queryMake": "Honda", "queryModel": "Accord", "queryModelYear": 2020, "odiNumber": "11747287", "manufacturer": "Honda (American Honda Motor Co.)", "crash": false, "fire": false, "numberOfInjuries": 0, "numberOfDeaths": 0, "dateOfIncident": "2026-05-05", "dateComplaintFiled": "2026-06-29", "vin": "1HGCV1F35LA", "components": ["UNKNOWN OR OTHER"], "componentText": "UNKNOWN OR OTHER", "summary": "All of the lights on my dash board is on", "sourceUrl": "https://api.nhtsa.gov/complaints/complaintsByVehicle?make=Honda&model=Accord&modelYear=2020", "scrapedAt": "2026-07-02T00:00:00.000Z" } ``` ### How to scrape NHTSA vehicle complaints 1. Open the actor on Apify. 2. Add one or more vehicle make/model/year combinations. 3. Set the maximum complaints per vehicle. 4. Choose the sort order. 5. Run the actor. 6. Download the dataset as JSON, CSV, Excel, XML, or via API. ### Tips for better results Use exact NHTSA-style make and model names. If a query returns no records, try common model spelling variants. For monitoring, schedule the same input weekly or monthly and compare new ODI numbers. For large portfolios, split vehicle groups by brand or model year to simplify downstream analysis. ### Integrations You can connect the dataset to: - Google Sheets for analyst review. - BigQuery or Snowflake for automotive data warehouses. - Webhooks for complaint monitoring alerts. - Make, Zapier, or n8n for no-code workflows. - Apify API clients for backend enrichment. ### API usage: Node.js ```js import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: process.env.APIFY_TOKEN }); const run = await client.actor('automation-lab/nhtsa-vehicle-complaints-scraper').call({ vehicles: [{ make: 'Honda', model: 'Accord', modelYear: 2020 }], maxComplaintsPerVehicle: 150, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items.length); ``` ### API usage: Python ```python from apify_client import ApifyClient import os client = ApifyClient(os.environ['APIFY_TOKEN']) run = client.actor('automation-lab/nhtsa-vehicle-complaints-scraper').call(run_input={ 'vehicles': [{'make': 'Honda', 'model': 'Accord', 'modelYear': 2020}], 'maxComplaintsPerVehicle': 150, }) items = client.dataset(run['defaultDatasetId']).list_items().items print(len(items)) ``` ### API usage: cURL ```bash curl -X POST "https://api.apify.com/v2/acts/automation-lab~nhtsa-vehicle-complaints-scraper/runs?token=$APIFY_TOKEN" \ -H 'Content-Type: application/json' \ -d '{"vehicles":[{"make":"Honda","model":"Accord","modelYear":2020}],"maxComplaintsPerVehicle":150}' ``` ### MCP integration Use Apify MCP with Claude Desktop or Claude Code to run this actor from natural language. MCP server URL: `https://mcp.apify.com/?tools=automation-lab/nhtsa-vehicle-complaints-scraper` Claude Code command: ```bash claude mcp add apify-nhtsa-complaints https://mcp.apify.com/?tools=automation-lab/nhtsa-vehicle-complaints-scraper ``` Claude Desktop JSON configuration: ```json { "mcpServers": { "apify-nhtsa-complaints": { "url": "https://mcp.apify.com/?tools=automation-lab/nhtsa-vehicle-complaints-scraper" } } } ``` Example prompts: - "Run the NHTSA vehicle complaints scraper for Honda Accord 2020 and summarize crash complaints." - "Extract complaints for Honda Civic 2020 and show the top components." - "Monitor Toyota Camry 2022 complaints and tell me if new fire-related reports appear." ### Scheduling monitoring jobs For recurring monitoring: 1. Create an Apify task with your target vehicles. 2. Schedule it weekly or monthly. 3. Export each run's dataset. 4. Deduplicate by `odiNumber`. 5. Alert when new complaints match your risk criteria. ### Common workflows #### Complaint volume comparison Run several vehicles and group rows by make, model, and year. #### Component monitoring Filter `components` for brakes, electrical, airbags, steering, power train, or unknown/other. #### Safety severity review Filter rows where `crash`, `fire`, `numberOfInjuries`, or `numberOfDeaths` is non-zero. #### Warranty signal enrichment Join `odiNumber`, component data, and summaries with internal claims or repair orders. ### Limitations The actor returns public complaint data exposed by NHTSA. It does not verify allegations, decode full VIN histories, or retrieve private owner contact information. NHTSA may redact or omit fields in source responses. ### Legality and privacy This actor queries a public government API. Use the output responsibly and comply with applicable privacy, consumer protection, and data-retention rules. Do not attempt to identify private individuals from complaint text. ### FAQ #### Why did my vehicle return zero complaints? The make/model/year combination may not exist in the NHTSA complaint API, or the model spelling may differ from your input. Try a known query such as Honda Accord 2020 to confirm the actor is running correctly. #### Why are some VIN values missing or partial? NHTSA source data may omit or redact VINs. The actor preserves what the API returns. #### Why are dates formatted differently than the website? The source returns dates as strings. The actor normalizes standard `MM/DD/YYYY` values to `YYYY-MM-DD` for easier sorting. ### Related scrapers Explore other Automation Lab actors for automotive, compliance, review, and public-record workflows: - https://apify.com/automation-lab/google-maps-lead-finder - https://apify.com/automation-lab/similarweb-scraper - https://apify.com/automation-lab/website-contact-finder ### Support If you need another NHTSA endpoint, recall workflow, VIN workflow, or output field, open an issue on the Apify actor page. ### Changelog #### 0.1 Initial private build for NHTSA vehicle complaint extraction. ### Field reference `odiNumber` is the best stable key for deduplication. `sourceUrl` records the exact API request. `products` is kept nested so downstream users can preserve the NHTSA object shape. `components` is split from the source component text to make filtering easier. ### Quality notes The actor is HTTP-only and uses no browser automation. The actor uses bounded retries for 429 and temporary 5xx API responses. The actor charges only after each complaint record is saved. ### Dataset export formats Apify lets you export the default dataset as: - JSON - JSONL - CSV - Excel - XML - RSS ### Final note NHTSA Vehicle Complaints Scraper is designed for reliable, repeatable, official-source complaint monitoring by vehicle make, model, and model year. # Actor input Schema ## `vehicles` (type: `array`): One or more make/model/model year combinations to query in the NHTSA complaints API. ## `make` (type: `string`): Optional single-vehicle shortcut. Used with model and modelYear if vehicles is empty. ## `model` (type: `string`): Optional single-vehicle shortcut. Used with make and modelYear if vehicles is empty. ## `modelYear` (type: `integer`): Optional single-vehicle shortcut. Used with make and model if vehicles is empty. ## `maxComplaintsPerVehicle` (type: `integer`): Maximum complaint records to save for each vehicle query. ## `maxItems` (type: `integer`): Safety cap across all vehicle searches. ## `sortBy` (type: `string`): Optional sort applied after the NHTSA API returns results. ## `includeProducts` (type: `boolean`): Include the nested NHTSA products array when present. ## Actor input object example ```json { "vehicles": [ { "make": "Honda", "model": "Accord", "modelYear": 2020 } ], "maxComplaintsPerVehicle": 20, "maxItems": 20, "sortBy": "dateComplaintFiledDesc", "includeProducts": true } ``` # Actor output Schema ## `overview` (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": "Honda", "model": "Accord", "modelYear": 2020 } ], "maxComplaintsPerVehicle": 20, "maxItems": 20, "sortBy": "dateComplaintFiledDesc", "includeProducts": true }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/nhtsa-vehicle-complaints-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": "Honda", "model": "Accord", "modelYear": 2020, }], "maxComplaintsPerVehicle": 20, "maxItems": 20, "sortBy": "dateComplaintFiledDesc", "includeProducts": True, } # Run the Actor and wait for it to finish run = client.actor("automation-lab/nhtsa-vehicle-complaints-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": "Honda", "model": "Accord", "modelYear": 2020 } ], "maxComplaintsPerVehicle": 20, "maxItems": 20, "sortBy": "dateComplaintFiledDesc", "includeProducts": true }' | apify call automation-lab/nhtsa-vehicle-complaints-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/nhtsa-vehicle-complaints-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "NHTSA Vehicle Complaints Scraper", "description": "Extract official NHTSA vehicle safety complaints by make, model, and model year for defect monitoring and automotive analytics.", "version": "0.1", "x-build-id": "Eih6yGqUwdQAAwM6J" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~nhtsa-vehicle-complaints-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-nhtsa-vehicle-complaints-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~nhtsa-vehicle-complaints-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-nhtsa-vehicle-complaints-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~nhtsa-vehicle-complaints-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-nhtsa-vehicle-complaints-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Vehicle searches", "type": "array", "description": "One or more make/model/model year combinations to query in the NHTSA complaints API.", "items": { "type": "object", "required": [ "make", "model", "modelYear" ], "properties": { "make": { "type": "string", "title": "Make", "description": "Vehicle make, for example Honda, Ford, Toyota." }, "model": { "type": "string", "title": "Model", "description": "Vehicle model, for example Accord, F-150, Camry." }, "modelYear": { "type": "integer", "title": "Model year", "description": "Four-digit model year.", "minimum": 1900, "maximum": 2030 } } } }, "make": { "title": "Single make shortcut", "type": "string", "description": "Optional single-vehicle shortcut. Used with model and modelYear if vehicles is empty." }, "model": { "title": "Single model shortcut", "type": "string", "description": "Optional single-vehicle shortcut. Used with make and modelYear if vehicles is empty." }, "modelYear": { "title": "Single model year shortcut", "minimum": 1900, "maximum": 2030, "type": "integer", "description": "Optional single-vehicle shortcut. Used with make and model if vehicles is empty." }, "maxComplaintsPerVehicle": { "title": "Max complaints per vehicle", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum complaint records to save for each vehicle query.", "default": 20 }, "maxItems": { "title": "Total max complaints", "minimum": 1, "maximum": 50000, "type": "integer", "description": "Safety cap across all vehicle searches.", "default": 20 }, "sortBy": { "title": "Sort complaints by", "enum": [ "dateComplaintFiledDesc", "dateIncidentDesc", "odiNumberDesc", "apiOrder" ], "type": "string", "description": "Optional sort applied after the NHTSA API returns results.", "default": "dateComplaintFiledDesc" }, "includeProducts": { "title": "Include product details", "type": "boolean", "description": "Include the nested NHTSA products array when present.", "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 } } } } } } } } } } ```