# AKC Dog Breed Directory Scraper (`jungle_synthesizer/akc-dog-breed-directory-scraper`) Actor Extract complete AKC breed profiles: trait scorecards, physical stats, colors, parent clubs, and popularity rankings for all recognized breeds and FSS candidates. - **URL**: https://apify.com/jungle\_synthesizer/akc-dog-breed-directory-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN 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. 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 ## AKC Dog Breed Directory Scraper Scrape breed profiles from the [American Kennel Club](https://www.akc.org/dog-breeds/). Returns structured data for every AKC-recognized breed and Foundation Stock Service candidate — names, breed groups, physical stats, trait scorecards, color standards, parent club links, and annual popularity rankings. ### AKC Dog Breed Directory Scraper Features - **Extracts 200+ breed profiles** from the full AKC directory, including recognized breeds and FSS candidates - **Returns the complete trait scorecard** — 9 numeric 1-5 ratings covering trainability, shedding, barking, energy, drooling, grooming frequency, and mental stimulation needs - **Collects physical standards** — height (inches), weight (lbs), and life expectancy ranges parsed from the breed standard - **Includes color and marking registries** — every AKC-accepted coat color and marking for each breed, as string arrays - **Captures parent club details** — national breed club name and URL for each recognized breed - **Pulls breed standard PDFs** — direct URL to the AKC's official per-breed standard document - **Flags AKC recognition status** — boolean distinguishes fully-recognized breeds from FSS candidates and Miscellaneous Class breeds - **Returns annual popularity ranks** — most recent AKC registration ranking (back to 2015) - **Runs on datacenter proxies** — no residential proxy required, no captcha ### What Can You Do With AKC Breed Data? - **Pet insurance carriers** — build risk-by-breed underwriting models using health disposition data and trait scores - **Breed-matching apps** — power quiz engines (exercise_needs, good_with_children scores) for apps like those from Hills or Purina - **AI training datasets** — label breed-identification models with canonical names, visual descriptions, and group classifications - **Pet commerce platforms** — enrich breed-indexed product catalogs with authoritative physical standards - **Content and affiliate sites** — generate breed comparison tables without maintaining the data manually ### How It Works 1. The scraper reads AKC's dedicated `breed-sitemap.xml`, which lists every breed detail page. No pagination to navigate, no letter-indexed crawling. 2. Each breed page is fetched and parsed. All structured data — traits, colors, clubs, history — is embedded server-side in the page source as a JSON blob. No browser required. 3. Physical stats (height, weight, life expectancy) are pulled from the page's JSON-LD Dataset schema. 4. The breed standard PDF URL comes from the `sameAs` field in the same JSON-LD block. 5. Results are collected and saved to the default Apify dataset, capped at `maxItems`. ### AKC Dog Breed Directory Scraper Input ```json { "maxItems": 10 } ```` | Field | Type | Default | Description | |-------|------|---------|-------------| | `maxItems` | integer | 10 | Maximum number of breed records to return. Set to 0 for all breeds (~250+). | ### AKC Dog Breed Directory Scraper Output Fields ```json { "breed_name": "Labrador Retriever", "breed_slug": "labrador-retriever", "breed_group": "Sporting Group", "akc_recognized": true, "akc_popularity_rank": 2, "height_inches": { "min": 22.5, "max": 24.5 }, "weight_lbs": { "min": 65, "max": 80 }, "life_expectancy_years": { "min": 11, "max": 13 }, "coat_type": "Double", "colors": ["Black", "Chocolate", "Yellow"], "markings": ["White Markings"], "temperament_traits": { "affectionate_with_family": 5, "good_with_young_children": 5, "good_with_other_dogs": 5, "openness_to_strangers": 5, "playfulness_level": 5, "watchdogprotective_nature": 3, "adaptability_level": 5 }, "exercise_needs": 5, "trainability": 5, "shedding_level": 4, "barking_level": 3, "energy_level": 5, "drooling_level": 2, "coat_grooming_frequency": 2, "mental_stimulation": 4, "history_text": "The Labrador Retriever is the traditional waterdog of Newfoundland...", "breed_standard_url": "https://images.akc.org/pdf/breeds/standards/LabradorRetriever.pdf", "parent_club_name": "Labrador Retriever Club, Inc.", "parent_club_url": "https://www.thelabradorclub.com", "hero_image_url": "https://www.akc.org/wp-content/uploads/2017/11/Labrador-Retrievers-three-colors.jpg", "profile_url": "https://www.akc.org/dog-breeds/labrador-retriever/", "scraped_at": "2026-05-30T13:39:03.888Z" } ``` | Field | Type | Description | |-------|------|-------------| | `breed_name` | string | Full AKC breed name | | `breed_slug` | string | URL slug used in the AKC directory | | `breed_group` | string | AKC group (Sporting, Hound, Working, Terrier, Toy, Non-Sporting, Herding, Miscellaneous Class, Foundation Stock Service) | | `akc_recognized` | boolean | True if the breed holds full AKC recognition (has a 4-digit year\_recognized) | | `akc_popularity_rank` | integer | Most recent annual AKC popularity rank by registration count | | `height_inches` | object | `{ min, max }` in inches — derived from the breed standard table | | `weight_lbs` | object | `{ min, max }` in pounds | | `life_expectancy_years` | object | `{ min, max }` in years | | `coat_type` | string | Coat type(s) per AKC standard (e.g. "Double", "Smooth", "Rough") | | `colors` | array | Accepted coat colors per AKC breed standard | | `markings` | array | Accepted markings | | `temperament_traits` | object | 7 rated dimensions (1-5): affectionate\_with\_family, good\_with\_young\_children, good\_with\_other\_dogs, openness\_to\_strangers, playfulness\_level, watchdogprotective\_nature, adaptability\_level | | `exercise_needs` | integer | 1-5 AKC energy level rating | | `trainability` | integer | 1-5 AKC trainability rating | | `shedding_level` | integer | 1-5 AKC shedding rating | | `barking_level` | integer | 1-5 AKC barking level rating | | `energy_level` | integer | 1-5 AKC energy level rating | | `drooling_level` | integer | 1-5 AKC drooling level rating | | `coat_grooming_frequency` | integer | 1-5 AKC grooming frequency rating | | `mental_stimulation` | integer | 1-5 AKC mental stimulation needs rating | | `history_text` | string | AKC breed history text (HTML stripped) | | `breed_standard_url` | string | URL to the AKC's official per-breed standard PDF | | `parent_club_name` | string | Name of the AKC national breed club | | `parent_club_url` | string | Website of the national breed club | | `hero_image_url` | string | URL of the primary breed photo from AKC | | `profile_url` | string | AKC breed page URL | | `scraped_at` | string | ISO 8601 timestamp of the scrape | ### 🔍 FAQ **How do I scrape AKC dog breed data?** AKC Dog Breed Directory Scraper handles everything. Set `maxItems` to the number of breeds you want, run it, and collect structured JSON. To get the full dataset of ~250+ breeds, set `maxItems` to 0. **What data can I get from the AKC dog breed directory?** AKC Dog Breed Directory Scraper returns 25+ fields per breed: the complete trait scorecard (9 numeric ratings), physical dimensions, registered colors and markings, parent club links, breed standard PDFs, AKC popularity rankings, and a full history text. It's the canonical AKC dataset in a single run. **How much does AKC Dog Breed Directory Scraper cost?** AKC Dog Breed Directory Scraper charges per record ($0.001/breed). Running the full dataset of ~250 breeds costs roughly $0.25 in compute. Cheaper than a dog license. **Does AKC Dog Breed Directory Scraper need proxies?** No. AKC's public dog breed directory serves data to anyone without bot detection. The scraper runs on standard datacenter IPs at moderate concurrency. **What is the AKC popularity rank?** Each year the AKC publishes a ranked list of breeds by registration count. `akc_popularity_rank` returns the most recent year's rank — rank 1 being the most popular. Not all breeds are ranked (FSS and Miscellaneous Class breeds often aren't). ### Why Use AKC Dog Breed Directory Scraper? - **First on Apify** — zero existing AKC-targeted actors on the store. Canonical source, canonical slot. - **Structured trait scorecards** — returns the 9 numeric ratings that power every dog-breed quiz and insurance underwriting model. Most scrapers don't touch structured data this deeply. - **No setup required** — point and run. The sitemap handles discovery; the server-rendered JSON handles extraction. You don't need to configure selectors or pagination. ### Need More Features? Need custom fields, additional filter options, or a different breed registry? [File an issue](https://console.apify.com/actors/issues) or get in touch. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of records to scrape ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 } ``` # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/akc-dog-breed-directory-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/akc-dog-breed-directory-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10 }' | apify call jungle_synthesizer/akc-dog-breed-directory-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/akc-dog-breed-directory-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AKC Dog Breed Directory Scraper", "description": "Extract complete AKC breed profiles: trait scorecards, physical stats, colors, parent clubs, and popularity rankings for all recognized breeds and FSS candidates.", "version": "0.1", "x-build-id": "LAxevAvEJtux0vHeK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~akc-dog-breed-directory-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-akc-dog-breed-directory-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jungle_synthesizer~akc-dog-breed-directory-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-akc-dog-breed-directory-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jungle_synthesizer~akc-dog-breed-directory-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-akc-dog-breed-directory-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records to scrape", "default": 10 } } }, "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": 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"example": 0 } } } } } } } } } } ```