# DoorDash Menu Scraper — Prices, Calories & Items | $0.59/1K (`bovi/doordash-scraper`) Actor Scrape **DoorDash** chain menus: **prices, calories, item modifiers/options, descriptions, images** + store rating, delivery fee & ETA. Cloudflare-free `/business/` path, no browser. **One record per menu item**, numeric prices, structural RSC parser with drift signal + fallback. - **URL**: https://apify.com/bovi/doordash-scraper.md - **Developed by:** [Vitalii Bondarev](https://apify.com/bovi) (community) - **Categories:** Other, MCP servers - **Stats:** 3 total users, 0 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.59 / 1,000 menu items 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 ## DoorDash Menu Scraper — Prices & Calories | from $1.50/1K | No Cloudflare Block Built for restaurant market analysts tracking chain pricing, nutrition app developers enriching food databases with calorie data, and franchise consultants benchmarking menu structures across competing chains. **Pricing:** Pay per menu item — $1.50/1K (full menu). First 10 items free. Never charged for failed or low-confidence parses (adaptive charging — your money is safe). **No Cloudflare. No Playwright. No browser required. Adaptive charging — never pay for bad data.** Scrape **DoorDash chain restaurant pages** and extract full menus with prices, calories, item descriptions, and restaurant metadata. Uses the Cloudflare-free `/business/` chain path — **no browser required, no Playwright overhead**. Returns one record per menu item. Structural RSC parser with `parse_confidence` drift detection. **Pay per menu item.** Get every Chipotle, McDonald's, or Starbucks menu item — with calories and prices — in one structured JSON output. --- ### vs. competitors DoorDash's consumer `/store/` pages sit behind Cloudflare and require a full browser (15–25s per restaurant, frequent breakage). Most scrapers target this path. This actor targets the `/business/` chain path — served **without** Cloudflare challenge and containing full menu data as RSC streaming payloads. No browser, no Playwright, fast. | Feature | This actor | Typical alternatives | |---|---|---| | Cloudflare challenge | No (uses `/business/` path) | Yes — 15–25s/store, fragile | | Prices | **Numeric** (`price_cents` + `price_usd`) | Strings like `"$8.50"` | | Item modifiers / options | **Yes** — option groups + per-option prices | No | | Store metadata on every row | Rating, delivery fee, ETA | Usually omitted | | Calories | Yes (null when undisclosed, not a fake `0`) | Often missing | | Item IDs | Yes (`item_id`) | Rarely | | Parser type | Structural RSC keys (no CSS classes) | CSS class-based (breaks on updates) | | Parser health signal | `parse_confidence` + `parse_source` + `warnings` | None | | Fallback when format drifts | **Yes** — RSC → `__NEXT_DATA__` → JSON scan | None (hard break) | | Charge on failure | **Never** | Often (broken runs still billed) | --- ### Output Schema — Per Menu Item | Field | Type | Description | |-------|------|-------------| | `restaurant_name` | string | Chain name, e.g. "Chipotle Mexican Grill" | | `business_id` | string | DoorDash store/business ID | | `city` | string | Store city | | `state` | string | Store state/region code | | `category` | string | Menu section name, e.g. "Entree", "Drinks" | | `item_name` | string | Menu item name | | `description` | string | Item description | | `price_cents` | integer | Price in cents (e.g. 1320 = $13.20) | | `price_usd` | float | Price in USD (e.g. 13.20) | | `calories` | number | Calorie count — `null` when the chain doesn't disclose it (never a misleading `0`) | | `options` | array | Option groups / modifiers: `[{name, min, max, options:[{name, price_usd, price_cents}]}]`. Empty list when the item has none. | | `image_url` | string | CDN image URL | | `item_id` | string | DoorDash item ID | | `is_popular` | boolean | Marked as popular/featured | | `rating` | float | Store average rating (repeated on each row) | | `num_ratings` | integer | Number of store ratings | | `delivery_fee` | string | Displayed delivery fee, e.g. `"$0.99"` | | `eta_minutes` | integer | Estimated delivery time in minutes | | `source_url` | string | The `/business/` URL scraped | | `parse_confidence` | float | 0.0–1.0 structural parse quality score | | `parse_source` | string | Which parser produced the row: `rsc` (primary) or `next_data` (fallback) | | `warnings` | array | Machine-readable drift signals | | `scraped_at` | string | ISO-8601 UTC timestamp | Each menu-item row is **self-contained** — it repeats the store name, rating, delivery fee, and ETA, so you can analyze a single row without joining back to a restaurant record. --- ### How to Use #### Option A — direct URLs ```json { "businessUrls": [ "https://www.doordash.com/business/chipotle-mexican-grill-115/", "https://www.doordash.com/business/mcdonald-s-36398/" ] } ```` Find the business URL by visiting any chain's DoorDash page and copying the `/business/` path URL. #### Option B — slug + ID ```json { "businesses": [ {"slug": "chipotle-mexican-grill", "businessId": "115"}, {"slug": "mcdonald-s", "businessId": "36398"} ] } ``` #### Bulk menu comparison ```json { "businessUrls": [ "https://www.doordash.com/business/chipotle-mexican-grill-115/", "https://www.doordash.com/business/taco-bell-6174/", "https://www.doordash.com/business/subway-3796/" ] } ``` *** ### Use Cases #### Restaurant menu intelligence Pull every item name, price, and calorie count from competing chains. Track price changes across locations or compare value-per-calorie across menus. #### Food delivery market research Analyze menu structure, category organization, and item naming conventions across fast-food chains. Identify menu gaps or pricing anomalies. #### Nutrition & calorie tracking apps Build or enrich food databases with DoorDash menu data. Filter by calorie count, price range, or `is_popular` flag. #### Franchise pricing analysis Compare prices for the same chain across different city/state combinations. Identify regional price variation in franchise menus. #### Competitive menu benchmarking Restaurants building new menus can compare their pricing and item structure against established chains at scale. *** ### Scope & Limitations **Supported**: DoorDash `/business/` chain pages only — these contain the full embedded menu without Cloudflare challenge. **Not supported**: Consumer `/store/` delivery pages (which show delivery ETA, address-gated menus, and real-time availability). Those require Playwright and are a Phase-2 add-on. - Menu items without a section name get `category: "Menu"` - Calories are `null` when the chain doesn't publicly disclose them (never a misleading `0`) - Prices reflect the chain's listed menu price, not delivery-fee-adjusted totals *** ### Proxy **RESIDENTIAL proxy is strongly recommended.** Datacenter IPs may be rate-limited on high-volume runs. The actor defaults to `useApifyProxy: true, groups: ["RESIDENTIAL"]`. Proxy usage is billed to the run owner at standard Apify platform pricing. *** ### Parser Resilience (the B-plan) RSC payload formats drift. This actor degrades gracefully instead of breaking: 1. **Primary — RSC parse.** Reassembles the React-Flight stream across `__next_f.push()` chunk boundaries (a single menu node frequently spans two pushes; naive parsers drop it). Nodes are matched by **stable keys/shape**, never by positional hex IDs or CSS classes. 2. **Fallback — `__NEXT_DATA__` / embedded JSON.** If no RSC stream is present, the actor harvests menu data from the legacy `__NEXT_DATA__` script or any inline `application/json` block. Rows are tagged `parse_source: "next_data"`. 3. **Fail-soft everywhere.** A truncated or changed node is skipped, never crashes the run. `parse_confidence` drops to reflect the gap. Every output record includes `parse_confidence` (0.0–1.0), `parse_source`, and `warnings`. A score below 0.5 signals likely structural change; below 0.3 the actor pushes records for transparency but **does not charge**. Apify's daily default-run health test catches drift before buyers report it. *** ### Pricing Pay per menu item scraped (`menu-item` event). A 50-item menu = 50 charges; a 150-item menu = 150 charges. You are **never** charged for: - the actor starting up, - failed or blocked fetches, - restaurants that return no items (you still get the store record, free), - low-confidence parses (`parse_confidence < 0.3`) — pushed for transparency, not billed. Set `maxItems` to cap spend: it's a strict budget enforced even mid-restaurant. *** ### Pricing example | Volume | Cost | |---|---| | 50 items (1 Chipotle) | $0.075 | | 100 items (~2 restaurants) | $0.15 | | 1,000 items (~15 restaurants) | $1.50 | | 10,000 items | $15.00 | A typical chain restaurant has 30–80 menu items. First 10 items free. Low-confidence parses (`parse_confidence < 0.3`) are pushed for transparency but not charged. ### FAQ **Do I need a DoorDash account or API key?** No. This actor uses the public `/business/` chain pages — no login, no credentials required. **Do I need a proxy?** RESIDENTIAL proxy is strongly recommended — datacenter IPs are commonly blocked by DoorDash on higher volumes. The actor defaults to `useApifyProxy: true, groups: ["RESIDENTIAL"]`. Proxy costs are billed to the run owner at standard Apify pricing. **What output formats are available?** JSON (default), CSV, and Excel — via the Apify dataset export or API. **What if the actor returns no menu items?** Ensure the URL is a `/business/` chain page (not a `/store/` consumer delivery page). If parsing fails, check `parse_confidence` in logs — a score below 0.5 means DoorDash's RSC format may have changed. The actor auto-retries with the `__NEXT_DATA__` fallback before giving up. ### Calorie data use case Nutrition app building example: scrape Chipotle's full menu, filter `calories > 0`, deduplicate by `item_name` — instant structured nutrition database. Health-conscious buyers pay a premium for calorie-guaranteed data. ### Use with AI agents (MCP) This actor is tagged `MCP_SERVERS` — compatible with Claude, GPT-4o, and other MCP-aware agents: ``` https://mcp.apify.com/?tools=bovi/doordash-scraper ``` *Not affiliated with DoorDash. Data is publicly available on doordash.com.* ### Integrations Built for restaurant market analysts and nutrition-app developers extracting chain menu prices and calorie data at scale — the JSON/dataset output drops into the tools you already run, no glue code: - **n8n / Make / Zapier** — trigger a run or pipe every new dataset item into 500+ apps (Google Sheets, Airtable, Slack, HubSpot, your database) with no code: [n8n](https://docs.apify.com/platform/integrations/n8n), [Make](https://docs.apify.com/platform/integrations/make), [Zapier](https://docs.apify.com/platform/integrations/zapier). - **Webhooks** — fire your own endpoint the moment a run finishes, to push results straight into your pipeline ([docs](https://docs.apify.com/platform/integrations/webhooks)). - **MCP server** — expose this actor as a tool to Claude, Cursor, or any [MCP client](https://mcp.apify.com) so an AI agent can pull this data mid-conversation ([guide](https://blog.apify.com/how-to-use-mcp/)). - **API & SDKs** — fetch the dataset as JSON, CSV, or Excel through the Apify REST API or the Python / JS SDKs. See all [Apify integrations](https://apify.com/integrations). # Actor input Schema ## `businessUrls` (type: `array`): List of DoorDash /business/ chain restaurant URLs to scrape. Each URL must be in the format https://www.doordash.com/business/{slug}-{businessId}/. Example: \['https://www.doordash.com/business/chipotle-mexican-grill-115/']. These pages are CF-free and return full menu data. ## `businesses` (type: `array`): Alternative input: list of {slug, businessId} objects. Slug is the URL-safe chain name (e.g. 'chipotle-mexican-grill'), businessId is the numeric DoorDash store ID. Example: \[{"slug": "chipotle-mexican-grill", "businessId": "115"}]. ## `maxItems` (type: `integer`): Hard cap on total menu item records returned across all URLs. 0 = unlimited. This is a strict budget: the actor stops charging once the cap is hit, even mid-restaurant — each menu item is exactly one PPE charge. A typical chain restaurant has 30–80 items. ## `requestDelay` (type: `number`): Seconds to wait between fetching consecutive URLs. Default 1.5s is polite and reduces ban risk. Increase for large batches. ## `proxyConfiguration` (type: `object`): Proxy settings. Default: Apify RESIDENTIAL proxy (strongly recommended — datacenter IPs are frequently blocked by DoorDash). Set useApifyProxy:true with groups:\["RESIDENTIAL"]. Buyers pay for proxy usage via Apify platform compute. ## Actor input object example ```json { "businessUrls": [ "https://www.doordash.com/business/chipotle-mexican-grill-115/" ], "maxItems": 0, "requestDelay": 1.5, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = { "businessUrls": [ "https://www.doordash.com/business/chipotle-mexican-grill-115/" ], "maxItems": 0 }; // Run the Actor and wait for it to finish const run = await client.actor("bovi/doordash-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 = { "businessUrls": ["https://www.doordash.com/business/chipotle-mexican-grill-115/"], "maxItems": 0, } # Run the Actor and wait for it to finish run = client.actor("bovi/doordash-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 '{ "businessUrls": [ "https://www.doordash.com/business/chipotle-mexican-grill-115/" ], "maxItems": 0 }' | apify call bovi/doordash-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=bovi/doordash-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "DoorDash Menu Scraper — Prices, Calories & Items | $0.59/1K", "description": "Scrape **DoorDash** chain menus: **prices, calories, item modifiers/options, descriptions, images** + store rating, delivery fee & ETA. Cloudflare-free `/business/` path, no browser. **One record per menu item**, numeric prices, structural RSC parser with drift signal + fallback.", "version": "0.1", "x-build-id": "VZNOnDovyV4fmhDHw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/bovi~doordash-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-bovi-doordash-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/bovi~doordash-scraper/runs": { "post": { "operationId": "runs-sync-bovi-doordash-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/bovi~doordash-scraper/run-sync": { "post": { "operationId": "run-sync-bovi-doordash-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": { "businessUrls": { "title": "Business Page URLs", "type": "array", "description": "List of DoorDash /business/ chain restaurant URLs to scrape. Each URL must be in the format https://www.doordash.com/business/{slug}-{businessId}/. Example: ['https://www.doordash.com/business/chipotle-mexican-grill-115/']. These pages are CF-free and return full menu data.", "items": { "type": "string" } }, "businesses": { "title": "Businesses (slug + ID)", "type": "array", "description": "Alternative input: list of {slug, businessId} objects. Slug is the URL-safe chain name (e.g. 'chipotle-mexican-grill'), businessId is the numeric DoorDash store ID. Example: [{\"slug\": \"chipotle-mexican-grill\", \"businessId\": \"115\"}].", "items": { "type": "object" } }, "maxItems": { "title": "Max Menu Items (total)", "minimum": 0, "maximum": 100000, "type": "integer", "description": "Hard cap on total menu item records returned across all URLs. 0 = unlimited. This is a strict budget: the actor stops charging once the cap is hit, even mid-restaurant — each menu item is exactly one PPE charge. A typical chain restaurant has 30–80 items.", "default": 0 }, "requestDelay": { "title": "Delay between requests (seconds)", "minimum": 0, "maximum": 30, "type": "number", "description": "Seconds to wait between fetching consecutive URLs. Default 1.5s is polite and reduces ban risk. Increase for large batches.", "default": 1.5 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings. Default: Apify RESIDENTIAL proxy (strongly recommended — datacenter IPs are frequently blocked by DoorDash). Set useApifyProxy:true with groups:[\"RESIDENTIAL\"]. Buyers pay for proxy usage via Apify platform compute.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```