# Amazon Reviews Scraper Pro (`ayeeyee/amazon-reviews-scraper-pro`) Actor Scrape Amazon product reviews across 20+ marketplaces with verified-purchase filtering, star/keyword filters, media extraction, and MCP-ready providerHealth. Multi-API fallback chain (Playwright + mobile HTML). 3 modes. No paid API keys. - **URL**: https://apify.com/ayeeyee/amazon-reviews-scraper-pro.md - **Developed by:** [Virtual Footprint LLC](https://apify.com/ayeeyee) (community) - **Categories:** Social media - **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 review extracteds 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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 ## Amazon Reviews Scraper Pro ![Apify](https://img.shields.io/badge/Apify-Actor-ff6b37?logo=apify) ![Version](https://img.shields.io/badge/version-1.0-blue) ![Pricing](https://img.shields.io/badge/pricing-PAY_PER_EVENT-success) ![Modes](https://img.shields.io/badge/modes-fast_lookup%7Cenrich%7Cbatch-orange) ![MCP-ready](https://img.shields.io/badge/MCP-ready-brightgreen) > Amazon product reviews at scale across 20+ marketplaces — verified-purchase filtering, star/keyword filters, media extraction, and MCP-ready providerHealth. Multi-API fallback chain. No paid API keys. --- ### Why This Actor Is Better The most reliable Amazon reviews scraper on the Apify Store. Built to outperform every incumbent on the three things that matter: coverage (20+ marketplaces), reliability (Playwright desktop + mobile HTML fallback), and signal quality (verified-purchase filter, star/keyword filters, media extraction, sentiment bands). Every review carries a confidenceScore and the actor emits providerHealth{} so MCP agents can route around failed providers. #### Key Features - 20+ marketplaces — amazon.com, .co.uk, .de, .fr, .it, .es, .ca, .com.au, .com.mx, .co.jp, .in, .com.br, .nl, .se, .pl, .sg, .com.tr, .ae, .sa - Multi-API fallback chain — Playwright desktop (JS pagination) primary, mobile HTML fallback when blocked - Verified-purchase filter — isolate the highest-trust reviews with one checkbox - Star + keyword filters — slice by rating range and body/title keyword - Media extraction — image and video URLs attached to reviews - Sentiment bands — automatic very_positive/positive/neutral/negative/very_negative classification - Confidence scoring — every review gets a 0.0-1.0 score weighted by verified status, body length, and media presence - Source attribution + providerHealth — MCP agents can route around failed providers - Cache-first mode — fast_lookup hits the Apify KVS cache for sub-second repeat queries - Transparent PPE pricing — $3/1K reviews, $1/1K verified, $0.50/1K with media --- ### Architecture ```` Input (queries + mode) | v \[Cache check] --hit--> return base data (<800ms) |miss v \[Primary provider: scrape\_amazon\_reviews\_desktop] |-- on failure --> \[Fallback provider] v \[Normalization + field mapping] | v \[Enrichment layer] | v \[Confidence scoring + source attribution + providerHealth] | v \[Progressive dataset push] (one push per result) | v \[Webhook + MCP-ready metadata] ```` Every result includes `providerHealth{}` tracking per-provider status, latency, and errors — making this actor safe to call from MCP agents that need to route around failures. --- ### Modes | Mode | Description | Target latency | Use case | |---|---|---|---| | `fast_lookup` | Cache-first, base data only | <800ms cached | Quick lookups, deduplication | | `enrich` | Full enrichment with contact extraction + scoring | ~2-4s/result | Detailed analysis | | `batch` | Queue-based, full enrichment, per-item isolation | varies | Large query lists (100+) | --- ### Input | Parameter | Type | Required | Default | Description | |---|---|:---:|---|---| | `mode` | string | — | `enrich` | `fast_lookup` \| `enrich` \| `batch` | | `queries` | array | yes | `["B08N5WRWNW"]` | Search queries | | `maxResults` | integer | — | `25` | Max results per query (1-1000) | | `webhookUrl` | string | — | — | Webhook for completion notification | #### Example input ```json { "mode": "enrich", "queries": ["B08N5WRWNW"], "maxResults": 50 } ```` *** ### Output Results are stored in the Apify dataset as structured JSON. See `.actor/output_schema.json` for the canonical schema. Every result includes: | Field | Type | Description | |---|---|---| | `confidenceScore` | number | 0.0-1.0 reliability score | | `sources` | array | Provider attribution | | `providerHealth` | object | Per-provider status/latency/error for MCP routing | | `cacheStatus` | string | `hit` | `miss` | `degraded` | | `mode` | string | Execution mode used | | `extractedAt` | string | ISO timestamp | *** ### Pricing Transparent pay-per-event (PPE) pricing. You only pay for successful results. | Event | Price | When charged | |---|---|---| | Actor Start | $0.05/1K runs | One-time per run | | Result | $0.003/result | Per result pushed | | Verified Review | $0.001/result | Charge per review marked 'Verified Purchase' (higher-value signal). | | Media Extracted | $0.0005/result | Charge per review with image/video media URLs extracted. | No monthly subscription required. *** ### Use Cases - Product research — aggregate review sentiment before launching a competing product - Brand monitoring — track review velocity and sentiment across your ASIN portfolio - SEO/ASO — extract review keywords to inform listing optimization - Market research — benchmark competitor review counts, ratings, and verified-purchase ratios - Reputation management — surface negative reviews with media for fast response - MCP agent workflows — call from LLM agents; providerHealth lets agents route around marketplace failures - QA / bug tracking — mine 1-2 star reviews for reproducible product issues - Influencer / reviewer outreach — build lists of high-helpful-vote reviewers *** ### Integration Examples #### Python (Apify SDK) ```python from apify_client import ApifyClient client = ApifyClient("YOUR_APIFY_TOKEN") run = client.actor("YOUR_USERNAME/amazon-reviews-scraper-pro").call(run_input={ "mode": "enrich", "queries": ["B08N5WRWNW"], "maxResults": 50, }) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) ``` #### cURL ```bash curl -X POST "https://api.apify.com/v2/acts/YOUR_USERNAME~amazon-reviews-scraper-pro/runs?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{"mode":"enrich","queries":["B08N5WRWNW"],"maxResults":25}' ``` #### MCP (Model Context Protocol) This actor is MCP-ready. Register it via `@apify/actors-mcp-server`: ```bash npx -y @apify/actors-mcp-server --tools actors,YOUR_USERNAME/amazon-reviews-scraper-pro ``` Agents can then call `call-actor` and use `providerHealth` + `confidenceScore` to route around failed providers and filter result quality. *** ### FAQ **Q: Do I need an Amazon API key?** No. This actor scrapes public review pages via Playwright + httpx. No Amazon Product Advertising API key or seller credentials required. **Q: Which marketplaces are supported?** 20+ marketplaces via the `marketplace` input: com, co.uk, de, fr, it, es, ca, com.au, com.mx, co.jp, in, com.br, nl, se, pl, sg, com.tr, ae, sa. Default is com. **Q: How does the fallback chain work?** The primary Playwright desktop scrape handles JS-rendered pagination. If Amazon blocks Playwright (CAPTCHA, 403, timeout), the actor falls back to a mobile-HTML httpx fetch. The providerHealth field on every result shows which providers succeeded and their latency. **Q: What does verified-purchase filtering do?** When `verifiedOnly` is true, only reviews marked 'Verified Purchase' by Amazon are returned. These are higher-trust signals for product research. **Q: How are reviews paginated?** The actor follows Amazon's review pagination (up to 50 pages on desktop, 10 on mobile fallback) until `maxReviewsPerProduct` is reached or the well runs dry. **Q: Can I call this from an LLM agent?** Yes. The actor is MCP-ready. Every result includes providerHealth{}, confidenceScore, ratingBand, and verifiedPurchase so agents can make routing and filtering decisions. *** ### Legal & Compliance This actor scrapes **publicly available** data. It does not access private data, bypass authentication, or store credentials. Users are responsible for complying with applicable data protection laws (GDPR, CCPA, etc.) and the target platform's Terms of Service. This actor is intended for legitimate research, analysis, and outreach use cases. It must not be used for spam, harassment, or unlawful activity. *** ### AI-DLC / Data Lifecycle This actor follows AI-DLC principles for ethical data handling: - **Collection** — Public data only; respects robots.txt and rate limits. - **Processing** — In-memory normalization; no PII logging. - **Storage** — Results are pushed to the user's Apify dataset, not retained by the actor. - **Usage** — Designed for analysis, enrichment, and legitimate outreach. - **Disposal** — No long-term caching of user data between runs (cache TTL 3600s for base results only). *** ### Enhancement Roadmap (API / MCP Integrations) - Multi-step orchestration via LangGraph conditional workflows - Vector store integration for semantic deduplication across runs - Additional paid enrichment APIs (user keys, disabled by default) *** ### Changelog - v1.0 — Initial release: 20+ marketplaces, Playwright+mobile fallback, verified-purchase filter, star/keyword filters, media extraction, MCP-ready metadata *** ### Links - **Apify Store:** https://apify.com/YOUR\_USERNAME/amazon-reviews-scraper-pro - **Documentation:** See this README - **Support:** Open an issue on the actor's Apify Store page # Actor input Schema ## `mode` (type: `string`): fast\_lookup: cache-first. enrich: multi-provider with media+sentiment. batch: queue-based. ## `queries` (type: `array`): ASINs (e.g. B08N5WRWNW) or full Amazon product URLs ## `maxResults` (type: `integer`): Maximum results per query (1-1000) ## `webhookUrl` (type: `string`): Optional webhook URL for completion notification ## `marketplace` (type: `string`): Amazon marketplace domain (default: com). Supports: com, co.uk, de, fr, it, es, ca, com.au, com.mx, co.jp, in, com.br, nl, se, pl, sg, com.tr, ae, sa ## `minRating` (type: `integer`): Only return reviews with this rating or higher (1-5). 0 = all ratings. ## `maxRating` (type: `integer`): Only return reviews with this rating or lower (1-5). 0 = all ratings. ## `verifiedOnly` (type: `boolean`): Only return reviews marked 'Verified Purchase'. ## `keywordFilter` (type: `string`): Only return reviews whose title or body contains this keyword (case-insensitive). ## `maxReviewsPerProduct` (type: `integer`): Hard cap on reviews returned per ASIN (default 100). ## `includeMedia` (type: `boolean`): Extract image/video URLs attached to reviews. ## Actor input object example ```json { "mode": "enrich", "queries": [ "B08N5WRWNW" ], "maxResults": 25, "webhookUrl": "", "marketplace": "com", "minRating": 0, "maxRating": 0, "verifiedOnly": false, "keywordFilter": "", "maxReviewsPerProduct": 100, "includeMedia": false } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("ayeeyee/amazon-reviews-scraper-pro").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 = {} # Run the Actor and wait for it to finish run = client.actor("ayeeyee/amazon-reviews-scraper-pro").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 '{}' | apify call ayeeyee/amazon-reviews-scraper-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ayeeyee/amazon-reviews-scraper-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Reviews Scraper Pro", "description": "Scrape Amazon product reviews across 20+ marketplaces with verified-purchase filtering, star/keyword filters, media extraction, and MCP-ready providerHealth. Multi-API fallback chain (Playwright + mobile HTML). 3 modes. No paid API keys.", "version": "1.0", "x-build-id": "GT05NH8BA0ecJY5Xg" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ayeeyee~amazon-reviews-scraper-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ayeeyee-amazon-reviews-scraper-pro", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ayeeyee~amazon-reviews-scraper-pro/runs": { "post": { "operationId": "runs-sync-ayeeyee-amazon-reviews-scraper-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ayeeyee~amazon-reviews-scraper-pro/run-sync": { "post": { "operationId": "run-sync-ayeeyee-amazon-reviews-scraper-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "queries" ], "properties": { "mode": { "title": "Execution Mode", "enum": [ "fast_lookup", "enrich", "batch" ], "type": "string", "description": "fast_lookup: cache-first. enrich: multi-provider with media+sentiment. batch: queue-based.", "default": "enrich" }, "queries": { "title": "Search Queries", "type": "array", "description": "ASINs (e.g. B08N5WRWNW) or full Amazon product URLs", "default": [ "B08N5WRWNW" ] }, "maxResults": { "title": "Max Results per Query", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum results per query (1-1000)", "default": 25 }, "webhookUrl": { "title": "Webhook URL", "type": "string", "description": "Optional webhook URL for completion notification", "default": "" }, "marketplace": { "title": "Marketplace", "type": "string", "description": "Amazon marketplace domain (default: com). Supports: com, co.uk, de, fr, it, es, ca, com.au, com.mx, co.jp, in, com.br, nl, se, pl, sg, com.tr, ae, sa", "default": "com" }, "minRating": { "title": "Minimum star rating", "type": "integer", "description": "Only return reviews with this rating or higher (1-5). 0 = all ratings.", "default": 0 }, "maxRating": { "title": "Maximum star rating", "type": "integer", "description": "Only return reviews with this rating or lower (1-5). 0 = all ratings.", "default": 0 }, "verifiedOnly": { "title": "Verified purchases only", "type": "boolean", "description": "Only return reviews marked 'Verified Purchase'.", "default": false }, "keywordFilter": { "title": "Keyword filter", "type": "string", "description": "Only return reviews whose title or body contains this keyword (case-insensitive).", "default": "" }, "maxReviewsPerProduct": { "title": "Max reviews per product", "type": "integer", "description": "Hard cap on reviews returned per ASIN (default 100).", "default": 100 }, "includeMedia": { "title": "Include review media", "type": "boolean", "description": "Extract image/video URLs attached to reviews.", "default": false } } }, "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 } } } } } } } } } } ```