# Chipotle Restaurant Details Scraper (`datacach/chipotle-restaurant-details-scraper`) Actor Extract Chipotle restaurant addresses, phone numbers, emails, GPS coordinates, and hours from store page URLs in bulk, structured JSON. - **URL**: https://apify.com/datacach/chipotle-restaurant-details-scraper.md - **Developed by:** [DataCach](https://apify.com/datacach) (community) - **Categories:** Developer tools, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.99 / 1,000 processed links 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/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 ## Chipotle Restaurant Details Scraper ### What is Chipotle Restaurant Details Scraper? Chipotle Restaurant Details Scraper is an **Apify Actor** that extracts full restaurant details for Chipotle US and Canada locations — **name, street address, city, state, ZIP code, phone number, GPS coordinates, and opening hours** — from the structured data embedded in each [locations.chipotle.com](https://locations.chipotle.com/) restaurant page. It takes a **list of Chipotle restaurant page URLs** as input — typically the output of the **[Chipotle Locations Scraper](https://apify.com/datacach/chipotle-locations-scraper)** Actor — and returns one clean, structured JSON record per restaurant, ready to export to **JSON, CSV, or Excel**. ### What can Chipotle Restaurant Details Scraper do? - 📍 Extract full address, city, state, and ZIP code for any Chipotle store page - ☎️ Pull the restaurant's phone number - 🌐 Pull precise GPS latitude/longitude coordinates - 🕒 Extract raw opening hours, including per-day schedules - 📥 Accept bulk input — paste hundreds of Chipotle store URLs at once - ⚙️ Control concurrency to balance speed vs. reliability - 🔄 Run on a **schedule** to keep restaurant data fresh over time - 🔌 Trigger runs and fetch results via the **Apify API** or SDKs (Python, JavaScript) - 🔗 Integrate with **Zapier, Make, and other Apify integrations** - 📊 Monitor runs and get alerted on failures directly from the Apify Console ### What data does Chipotle Restaurant Details Scraper extract? | Field | Description | |---|---| | `name` | Restaurant name (e.g. "Chipotle Mexican Grill") | | `street` | Street address | | `city` | City | | `state` | State / province code | | `zipcode` | ZIP / postal code | | `phone` | Restaurant phone number | | `latitude` | GPS latitude | | `longitude` | GPS longitude | | `hours_raw` | Raw opening hours (weekly schedule + per-day specification) | | `store_number` | Chipotle's internal store number (parsed from the store's email address) | | `yext_entity_id` | Yext entity ID for the store page (Yext powers locations.chipotle.com) | | `email` | Store contact email address | | `url` | Source restaurant page URL | | `extraction_datetime` | Timestamp (UTC, ISO 8601) when the record was extracted | | `extraction_date` | Extraction date (mm-dd-yyyy) | ### How do I scrape Chipotle restaurant details? 1. Run the **[Chipotle Locations Scraper](https://apify.com/datacach/chipotle-locations-scraper)** Actor (or otherwise collect Chipotle restaurant page URLs). 2. Open this Actor's **Input** tab and paste the URLs into the `links` field. 3. Optionally adjust `maxConcurrency` (default: 5) to control how many pages are fetched in parallel. 4. Click **Start** and download your results from the **Output** tab in JSON, CSV, or Excel. ### Input This Actor takes two simple inputs: - **Restaurant URLs** (`links`, required) — a list of Chipotle restaurant page URLs, e.g. `https://locations.chipotle.com/al/birmingham/300-20th-st-s`. Typically produced by the [Chipotle Locations Scraper](https://apify.com/datacach/chipotle-locations-scraper) Actor. - **Max concurrency** (`maxConcurrency`, optional, default `5`) — how many restaurant pages are fetched in parallel. Higher values finish faster; lower values are gentler on the source site and more reliable. ![Chipotle Restaurant Details Scraper input example](https://github.com/BenjaminFloresV/public-datacach-apify-actors-media/blob/main/chipotle-restaurant-details-scraper/chipotle-restaurant-detail-scraper-input-example.png?raw=true) ### Free vs. paid Apify account: what changes? This Actor behaves the same way for everyone — the only difference is **how many restaurant URLs get processed per run**, based on your Apify account plan: | | Free plan | Paid plan | |---|---|---| | URLs processed per run | First **5** URLs only (extra URLs in your input are ignored) | **All** URLs you provide — no cap | | Concurrency control (`maxConcurrency`) | ✅ Available | ✅ Available | | Output fields | Same full set (address, phone, GPS, hours) | Same full set (address, phone, GPS, hours) | | Scheduling, API access, integrations | ✅ Available | ✅ Available | If you're on the free plan and need to process a full list of URLs, either **upgrade your Apify plan** or split your URLs into batches of 5 and run the Actor multiple times. ### Output example ```json { "url": "https://locations.chipotle.com/al/auburn/1700-opelika-rd", "name": "Chipotle Mexican Grill", "street": "1700 Opelika Rd", "city": "Auburn", "state": "AL", "zipcode": "36830", "phone": "+13344661903", "latitude": 32.6250055, "longitude": -85.4452043, "hours_raw": { "openingHours": ["Mo,Tu,We,Th,Fr,Sa,Su 10:45-23:00"], "openingHoursSpecification": [ { "@type": "OpeningHoursSpecification", "dayOfWeek": "https://schema.org/Monday", "opens": "10:45", "closes": "23:00" } ] }, "store_number": "5255", "yext_entity_id": "1066793958", "email": "AL.5255.AuburnMall@chipotle.com", "extraction_datetime": "2026-07-22T02:13:06.147276+00:00", "extraction_date": "07-22-2026" } ```` You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. ### Use cases - **Store locator data** — power an internal store finder or map with accurate Chipotle address and GPS data. - **Franchise & market research** — analyze Chipotle's store footprint, density, and hours by state or region. - **Data enrichment** — enrich an existing list of Chipotle locations with phone numbers, coordinates, and hours. - **Competitive intelligence** — track opening hours and store counts alongside other QSR chains. - **Logistics & delivery integrations** — feed accurate restaurant addresses and coordinates into routing or delivery systems. ### Chipotle-related Actors | Actor | What it does | |---|---| | [Chipotle Locations Scraper](https://apify.com/datacach/chipotle-locations-scraper) | Collects the list of Chipotle restaurant page URLs — feed its output into this Actor | | Chipotle Restaurant Details Scraper (this Actor) | Extracts full details for each Chipotle restaurant URL | ### FAQ #### Is it legal to scrape Chipotle restaurant data? This Actor only extracts publicly available, structured data (schema.org markup) already published on Chipotle's own restaurant pages, similar to what search engines index. Scraping public data is generally legal, but you're responsible for complying with the target site's Terms of Service and applicable laws in your jurisdiction. Avoid scraping personal data or content behind a login. #### Does this Actor have an API? Yes. Every Apify Actor is automatically exposed as an API. You can start runs, retrieve results, and integrate this Actor into your own applications using the [Apify API](https://docs.apify.com/api/v2) or the official SDKs for Python and JavaScript. #### Can I schedule this Actor to run automatically? Yes. Use the Apify Console's **Scheduler** to run this Actor on a recurring basis, so your Chipotle restaurant data stays up to date without manual intervention. #### Why did some restaurant URLs return no data? A small number of pages may be temporarily blocked by anti-bot protection or missing the expected structured data. Re-running the Actor for those specific URLs usually resolves transient issues. #### What if I need something more custom? If you need a modified version of this Actor — different fields, a different Chipotle domain, or a fully custom scraper — reach out via the Issues tab or request a custom solution from the Apify team. ### Support Found a bug or have a feature request? Open an issue on this Actor's **Issues** tab in Apify Console. For custom scraping solutions tailored to your needs, contact Apify or the Actor's developer directly. # Actor input Schema ## `links` (type: `array`): Chipotle restaurant page URLs to extract metadata from, e.g. https://locations.chipotle.com/al/birmingham/300-20th-st-s. Typically the output of the Chipotle Locations Scraper Actor. Free plan accounts process only the first 5 URLs. ## `maxConcurrency` (type: `integer`): Maximum number of restaurant pages fetched in parallel. Higher values finish the run faster but increase the chance of being rate-limited or blocked; lower values are gentler and more reliable. ## Actor input object example ```json { "links": [ "https://locations.chipotle.com/al/birmingham/300-20th-st-s", "https://locations.chipotle.com/al/auburn/1700-opelika-rd" ], "maxConcurrency": 5 } ``` # Actor output Schema ## `dataset` (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 = { "links": [ "https://locations.chipotle.com/al/birmingham/300-20th-st-s", "https://locations.chipotle.com/al/auburn/1700-opelika-rd" ] }; // Run the Actor and wait for it to finish const run = await client.actor("datacach/chipotle-restaurant-details-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 = { "links": [ "https://locations.chipotle.com/al/birmingham/300-20th-st-s", "https://locations.chipotle.com/al/auburn/1700-opelika-rd", ] } # Run the Actor and wait for it to finish run = client.actor("datacach/chipotle-restaurant-details-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 '{ "links": [ "https://locations.chipotle.com/al/birmingham/300-20th-st-s", "https://locations.chipotle.com/al/auburn/1700-opelika-rd" ] }' | apify call datacach/chipotle-restaurant-details-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=datacach/chipotle-restaurant-details-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Chipotle Restaurant Details Scraper", "description": "Extract Chipotle restaurant addresses, phone numbers, emails, GPS coordinates, and hours from store page URLs in bulk, structured JSON.", "version": "0.0", "x-build-id": "rCeDSHIP7M6Een09h" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/datacach~chipotle-restaurant-details-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-datacach-chipotle-restaurant-details-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/datacach~chipotle-restaurant-details-scraper/runs": { "post": { "operationId": "runs-sync-datacach-chipotle-restaurant-details-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/datacach~chipotle-restaurant-details-scraper/run-sync": { "post": { "operationId": "run-sync-datacach-chipotle-restaurant-details-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "links" ], "properties": { "links": { "title": "Restaurant URLs", "type": "array", "description": "Chipotle restaurant page URLs to extract metadata from, e.g. https://locations.chipotle.com/al/birmingham/300-20th-st-s. Typically the output of the Chipotle Locations Scraper Actor. Free plan accounts process only the first 5 URLs.", "items": { "type": "string" } }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum number of restaurant pages fetched in parallel. Higher values finish the run faster but increase the chance of being rate-limited or blocked; lower values are gentler and more reliable.", "default": 5 } } }, "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 } } } } } } } } } } ```