# Car Complaints Scraper (`kamikaze28/carcomplaintscrawler`) Actor Scrapes car complaint data from CarComplaints.com — by make, model, year, and complaint category — including NHTSA complaint counts. - **URL**: https://apify.com/kamikaze28/carcomplaintscrawler.md - **Developed by:** [Seth](https://apify.com/kamikaze28) (community) - **Categories:** Developer tools, Other, Open source - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Car Complaints Crawler ### What does Car Complaints Crawler do? **Car Complaints Crawler** scrapes vehicle complaint data from [CarComplaints.com](https://www.carcomplaints.com) — one of the most comprehensive consumer-reported car problem databases on the web. For every make, model, year, and complaint category, it collects both user-submitted complaint counts and NHTSA (National Highway Traffic Safety Administration) complaint counts. Run it once to get a full snapshot of the database, or schedule it weekly to track how complaint volumes change over time. Results are available for download as JSON, CSV, or Excel directly from the Apify Console. ### Why use Car Complaints Crawler? - **Automotive research** — identify which vehicles have the most reported problems before buying - **Legal and lemon law research** — find patterns in complaints by make, model, year, and category - **Journalism and data analysis** — track complaint trends across manufacturers - **Competitive intelligence** — benchmark reliability data across brands - **Insurance and risk modeling** — supplement actuarial data with real-world complaint volume ### How to use Car Complaints Crawler 1. Click **Try for free** on this page 2. Optionally enter one or more makes to limit the crawl (leave blank to scrape everything) 3. Optionally filter by model, minimum year, or maximum year 4. Click **Start** and wait for the run to complete 5. Download your dataset as JSON, CSV, or Excel from the **Output** tab A full crawl of all makes covers 70+ manufacturers, hundreds of models, and thousands of year/category combinations. It typically completes in a few hours. For a quick test, set **Max requests per crawl** to 50. ### Input | Field | Type | Description | |---|---|---| | Filter by make(s) | string list | Limit to specific makes, e.g. `Ford`, `Toyota`. Leave empty for all. | | Filter by model(s) | string list | Limit to specific models, e.g. `F-150`, `Camry`. Used together with make filter. | | Minimum year | integer | Only include model years at or above this value. | | Maximum year | integer | Only include model years at or below this value. | | Max requests per crawl | integer | Cap total HTTP requests (useful for testing). `0` = unlimited. | Example input to scrape only Ford and Toyota from 2015 onward: ```json { "makes": ["Ford", "Toyota"], "minYear": 2015 } ```` ### Output Each record represents one complaint category for a specific make/model/year. You can download the dataset in various formats such as JSON, CSV, or Excel. Example output records: ```json [ { "make": "Ford", "model": "F-150", "year": "2018", "year_complaints": "312", "model_total_complaints": "4821", "category": "engine problems", "category_complaints": "87", "nhtsa_complaints": "204", "url": "https://www.carcomplaints.com/Ford/F-150/2018/" }, { "make": "Ford", "model": "F-150", "year": "2018", "year_complaints": "312", "model_total_complaints": "4821", "category": "transmission problems", "category_complaints": "43", "nhtsa_complaints": "98", "url": "https://www.carcomplaints.com/Ford/F-150/2018/" } ] ``` ### Data fields | Field | Description | |---|---| | `make` | Vehicle manufacturer (e.g. Ford, Toyota) | | `model` | Vehicle model name (e.g. F-150, Camry) | | `year` | Model year | | `year_complaints` | Total user complaints for this make/model/year | | `model_total_complaints` | Total user complaints across all years for this model | | `category` | Complaint category (e.g. engine problems, transmission problems) | | `category_complaints` | User complaints for this category/year | | `nhtsa_complaints` | NHTSA complaints for this category/year | | `url` | Source page URL | ### Pricing and cost A full crawl of all 70+ makes costs approximately 5–15 compute units depending on the size of the database at run time. Using make/model/year filters dramatically reduces cost for targeted use cases. ### Tips - Use **Filter by make(s)** to run targeted, low-cost scrapes for specific brands - Set **Max requests per crawl** to `50` to do a quick test run before committing to a full crawl - Schedule a weekly run to track complaint trends over time — new complaints are submitted daily ### FAQ and support - **Is this legal?** This Actor scrapes publicly available data from CarComplaints.com. Always review a website's Terms of Service before using scraped data commercially. - **The data looks incomplete** — some year/category combinations have no user complaints but do have NHTSA complaints. This is expected; `category_complaints` will be `null` in those cases. - **Found a bug or need a custom feature?** Open an issue on the Actor's Issues tab. # Actor input Schema ## `makes` (type: `array`): Limit the crawl to specific car makes (e.g. Ford, Toyota). Leave empty to crawl all makes. ## `models` (type: `array`): Limit the crawl to specific models (e.g. F-150, Camry). Only applies when makes are also filtered. Leave empty for all models. ## `minYear` (type: `integer`): Only include model years at or above this value. Leave blank for all years. ## `maxYear` (type: `integer`): Only include model years at or below this value. Leave blank for all years. ## `maxRequestsPerCrawl` (type: `integer`): Safety limit on total HTTP requests. Useful for testing. 0 = unlimited. ## Actor input object example ```json { "makes": [ "Kia" ], "models": [ "Sedona" ], "maxRequestsPerCrawl": 0 } ``` # 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 = { "makes": [ "Kia" ], "models": [ "Sedona" ] }; // Run the Actor and wait for it to finish const run = await client.actor("kamikaze28/carcomplaintscrawler").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 = { "makes": ["Kia"], "models": ["Sedona"], } # Run the Actor and wait for it to finish run = client.actor("kamikaze28/carcomplaintscrawler").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 '{ "makes": [ "Kia" ], "models": [ "Sedona" ] }' | apify call kamikaze28/carcomplaintscrawler --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=kamikaze28/carcomplaintscrawler", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Car Complaints Scraper", "description": "Scrapes car complaint data from CarComplaints.com — by make, model, year, and complaint category — including NHTSA complaint counts.", "version": "0.1", "x-build-id": "VtIld0fxk0nJaLgrg" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/kamikaze28~carcomplaintscrawler/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-kamikaze28-carcomplaintscrawler", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/kamikaze28~carcomplaintscrawler/runs": { "post": { "operationId": "runs-sync-kamikaze28-carcomplaintscrawler", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/kamikaze28~carcomplaintscrawler/run-sync": { "post": { "operationId": "run-sync-kamikaze28-carcomplaintscrawler", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "makes": { "title": "Filter by make(s)", "type": "array", "description": "Limit the crawl to specific car makes (e.g. Ford, Toyota). Leave empty to crawl all makes.", "default": [ "Kia" ], "items": { "type": "string" } }, "models": { "title": "Filter by model(s)", "type": "array", "description": "Limit the crawl to specific models (e.g. F-150, Camry). Only applies when makes are also filtered. Leave empty for all models.", "default": [ "Sedona" ], "items": { "type": "string" } }, "minYear": { "title": "Minimum year", "minimum": 1980, "maximum": 2030, "type": "integer", "description": "Only include model years at or above this value. Leave blank for all years." }, "maxYear": { "title": "Maximum year", "minimum": 1980, "maximum": 2030, "type": "integer", "description": "Only include model years at or below this value. Leave blank for all years." }, "maxRequestsPerCrawl": { "title": "Max requests per crawl", "minimum": 0, "type": "integer", "description": "Safety limit on total HTTP requests. Useful for testing. 0 = unlimited.", "default": 0 } } }, "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 } } } } } } } } } } ```