# Amazon Autocomplete Keyword Scraper (`agency-shift/amazon-autocomplete-keywords`) Actor Get Amazon autocomplete suggestions for any search term. Uncover what customers are actually searching for. Essential for product research and ecommerce SEO. - **URL**: https://apify.com/agency-shift/amazon-autocomplete-keywords.md - **Developed by:** [Valdeir Lima](https://apify.com/agency-shift) (community) - **Categories:** SEO tools, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing $0.03 / actor start 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 ## Amazon Autocomplete Keyword Scraper **Expand any seed into hundreds of real Amazon search suggestions** — the autocomplete keywords real shoppers type. A fast **Amazon keyword research tool** for sellers, FBA, listing optimization and PPC. Multi-marketplace (US, UK, DE, FR, ES, IT, CA, BR, IN, JP). No API key. ### What it does - Takes seed keywords and expands them with **A–Z** and prefix modifiers - Returns **unique, real Amazon Autocomplete suggestions** (buyer-intent search terms) - Works across 10 Amazon marketplaces ### Use cases - **Amazon SEO / listing optimization** — find high-intent keywords for titles & bullets - **PPC / Sponsored Products** — discover keywords and negatives - **Product research** — see what shoppers search around a niche - **Cross-market** — compare demand across US/EU marketplaces ### Input | Field | Type | Default | Description | |---|---|---|---| | `seeds` | array | — | Seed keywords/products | | `marketplace` | string | `us` | us/uk/de/fr/es/it/ca/br/in/jp | | `expansions` | array | `["alphabet"]` | `alphabet`, `prefixes` | ### Output ```json { "seed": "yoga mat", "keyword": "yoga mat non slip", "marketplace": "us", "source": "yoga mat n" } ```` One seed typically yields 100–250 keyword ideas. ### FAQ **API key?** None. **Does it return search volume?** No — these are keyword *ideas* (real Amazon suggestions). Pair with a volume tool for numbers. **Which marketplaces?** US, UK, DE, FR, ES, IT, CA, BR, IN, JP. # Actor input Schema ## `seeds` (type: `array`): Base keywords/products to expand (e.g. 'yoga mat'). ## `marketplace` (type: `string`): Which Amazon site to query. ## `expansions` (type: `array`): Modifier sets to apply to each seed. ## Actor input object example ```json { "seeds": [ "yoga mat" ], "marketplace": "us", "expansions": [ "alphabet" ] } ``` # 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 = { "seeds": [ "yoga mat" ] }; // Run the Actor and wait for it to finish const run = await client.actor("agency-shift/amazon-autocomplete-keywords").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 = { "seeds": ["yoga mat"] } # Run the Actor and wait for it to finish run = client.actor("agency-shift/amazon-autocomplete-keywords").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 '{ "seeds": [ "yoga mat" ] }' | apify call agency-shift/amazon-autocomplete-keywords --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=agency-shift/amazon-autocomplete-keywords", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Autocomplete Keyword Scraper", "description": "Get Amazon autocomplete suggestions for any search term. Uncover what customers are actually searching for. Essential for product research and ecommerce SEO.", "version": "0.0", "x-build-id": "FPMqXxn0Pbmj8aLFa" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/agency-shift~amazon-autocomplete-keywords/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-agency-shift-amazon-autocomplete-keywords", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/agency-shift~amazon-autocomplete-keywords/runs": { "post": { "operationId": "runs-sync-agency-shift-amazon-autocomplete-keywords", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/agency-shift~amazon-autocomplete-keywords/run-sync": { "post": { "operationId": "run-sync-agency-shift-amazon-autocomplete-keywords", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "seeds" ], "properties": { "seeds": { "title": "Seed keywords", "type": "array", "description": "Base keywords/products to expand (e.g. 'yoga mat').", "items": { "type": "string" } }, "marketplace": { "title": "Amazon marketplace", "enum": [ "us", "uk", "de", "fr", "es", "it", "ca", "br", "in", "jp" ], "type": "string", "description": "Which Amazon site to query.", "default": "us" }, "expansions": { "title": "Expansion sets", "type": "array", "description": "Modifier sets to apply to each seed.", "items": { "type": "string", "enum": [ "alphabet", "prefixes" ] }, "default": [ "alphabet" ] } } }, "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 } } } } } } } } } } ```