# Keyword Discovery — Autocomplete, PAA & Related Searches (`accurate_pouch/keyword-discovery`) Actor Scrapes Google Autocomplete suggestions (with a-z expansion), People Also Ask questions, and Related Searches for any seed keyword. Returns structured keyword ideas with source labels. No search volume or keyword difficulty — pure discovery. $0.003/query. - **URL**: https://apify.com/accurate\_pouch/keyword-discovery.md - **Developed by:** [Manchitt Sanan](https://apify.com/accurate_pouch) (community) - **Categories:** SEO tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Keyword Discovery — Autocomplete, PAA & Related Searches Discover keyword ideas from three Google sources using a single seed keyword. No paid API keys needed. ### What It Returns - **Autocomplete suggestions** — Google's type-ahead predictions, including a-z letter expansion (e.g., "seed a", "seed b", ...) for broader coverage - **People Also Ask (PAA) questions** — Questions Google surfaces in the "People also ask" SERP feature - **Related Searches** — Terms from the "Related searches" section at the bottom of Google results ### Quick Start ```json { "keywords": ["best web scraper 2026"], "expandAlphabet": true, "dryRun": false } ```` ### Input | Field | Type | Required | Default | Description | |---|---|---|---|---| | `keywords` | string\[] | Yes | — | Seed keywords to expand | | `expandAlphabet` | boolean | No | `true` | Append a-z to seed for deeper autocomplete discovery | | `dryRun` | boolean | No | `false` | Log what would be done without fetching data | ### Output Example ```json { "seed": "best web scraper 2026", "autocomplete": [ "best web scraper 2026 free", "best web scraper 2026 reddit", "best web scraper for beginners", "best web scraper chrome extension" ], "peopleAlsoAsk": [ "What is the best web scraper in 2026?", "Is web scraping legal?", "What is the easiest web scraper to use?" ], "relatedSearches": [ "web scraper tools", "free web scraping software", "python web scraper" ], "totalDiscovered": 10 } ``` ### Pricing **$0.003 per seed keyword** processed (pay-per-event via Apify platform charging). Free tier limit: 0 (all usage is charged). ### Limitations - **No search volume data** — this actor discovers keywords, it does not estimate monthly search volume (that requires paid APIs like SEMrush, Ahrefs, or Google Ads API) - **No keyword difficulty (KD)** — same reason; KD scoring requires backlink/SERP analysis APIs - **Google may block requests** — from datacenter IPs, Google may return CAPTCHAs or empty results. The actor handles this gracefully and returns whatever data it gets - **PAA and Related Searches extraction is regex-based** — Google changes its HTML structure frequently; results may vary ### Related Tools by manchittlab - [Broken Link Checker](https://apify.com/manchittlab/broken-link-checker) — Crawl any site and find broken links - [SERP Scraper](https://apify.com/manchittlab/serp-scraper) — Scrape Google search results - [Email Scraper](https://apify.com/manchittlab/email-scraper) — Extract emails from any website ## Tue Apr 14 22:51:12 IST 2026 # Actor input Schema ## `keywords` (type: `array`): List of seed keywords to discover related terms for ## `expandAlphabet` (type: `boolean`): Append each letter a-z to the seed and fetch autocomplete for each. Generates many more suggestions but takes longer. ## `dryRun` (type: `boolean`): If true, logs what would be done without actually fetching data. Useful for testing input. ## Actor input object example ```json { "keywords": [ "best web scraper 2026" ], "expandAlphabet": true, "dryRun": false } ``` # 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 = { "keywords": [ "best web scraper 2026" ] }; // Run the Actor and wait for it to finish const run = await client.actor("accurate_pouch/keyword-discovery").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 = { "keywords": ["best web scraper 2026"] } # Run the Actor and wait for it to finish run = client.actor("accurate_pouch/keyword-discovery").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 '{ "keywords": [ "best web scraper 2026" ] }' | apify call accurate_pouch/keyword-discovery --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=accurate_pouch/keyword-discovery", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Keyword Discovery — Autocomplete, PAA & Related Searches", "description": "Scrapes Google Autocomplete suggestions (with a-z expansion), People Also Ask questions, and Related Searches for any seed keyword. Returns structured keyword ideas with source labels. No search volume or keyword difficulty — pure discovery. $0.003/query.", "version": "0.1", "x-build-id": "bKy4hcNcoXb2FKZDx" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/accurate_pouch~keyword-discovery/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-accurate_pouch-keyword-discovery", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/accurate_pouch~keyword-discovery/runs": { "post": { "operationId": "runs-sync-accurate_pouch-keyword-discovery", "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/accurate_pouch~keyword-discovery/run-sync": { "post": { "operationId": "run-sync-accurate_pouch-keyword-discovery", "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": [ "keywords" ], "properties": { "keywords": { "title": "Seed Keywords", "type": "array", "description": "List of seed keywords to discover related terms for", "items": { "type": "string" } }, "expandAlphabet": { "title": "Expand with A-Z", "type": "boolean", "description": "Append each letter a-z to the seed and fetch autocomplete for each. Generates many more suggestions but takes longer.", "default": true }, "dryRun": { "title": "Dry Run", "type": "boolean", "description": "If true, logs what would be done without actually fetching data. Useful for testing input.", "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 } } } } } } } } } } ```