# Free Keyword Research Tool for SEO — Volume + CPC (`s-r/google-keywords`) Actor Free keyword research tool for SEO. Combines Google Autocomplete with monthly search volume, CPC, SEO difficulty, paid difficulty, and search intent classification for any seed keyword in 50+ countries and languages. - **URL**: https://apify.com/s-r/google-keywords.md - **Developed by:** [SR](https://apify.com/s-r) (community) - **Categories:** AI - **Stats:** 2 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing $2.00 / 1,000 keyword analyzeds 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 ## Free Keyword Research Tool for SEO — Volume + CPC + Difficulty The free keyword research tool for SEO. Discover keywords related to any seed term with **monthly search volume**, **CPC**, **SEO difficulty**, **paid difficulty**, **competition score**, and **search intent classification** — for any of 50+ countries and languages. Combines free Google Autocomplete (a-z + 0-9 alphabet expansion) with a managed keyword-info backend to give you a complete picture of demand around any keyword in seconds. ### What you get Per keyword variant: - **Monthly search volume** (12-month trend included) - **Average CPC** in local currency + USD - **SEO difficulty** (0-100, lower = easier to rank) - **Paid difficulty** (0-100) - **Competition score** (0-1) - **Search intent**: Info / Nav / Commercial / Transactional - **Global volume breakdown** by country ### Why use this keyword research tool for SEO Ahrefs Keywords Explorer costs $99-$399/month. Semrush Keyword Magic Tool costs $129-$449/month. Both gate volume + difficulty data behind a subscription. This Actor: - Returns **the same fields** — volume, CPC, SD, PD, intent - Pulls **autocomplete-expanded keyword variants** automatically - Works across **50+ countries** with localized volume data - Has **no subscription** — pay only for the keywords you research ### Input | Field | Default | Description | |---|---|---| | `keyword` | required | Seed keyword to research (e.g. `running shoes`) | | `country` | `us` | ISO 2-letter country code | | `language` | `en` | ISO 2-letter language code | | `limit` | 100 | Max keyword variants to return (1-500) | | `max_suggestions` | 0 (all) | Cap autocomplete expansions before volume lookup | | `min_volume` | 10 | Drop keywords below this monthly volume | | `concurrency` | 10 | Concurrent API requests (lower if rate-limited) | ### Output (sample) ```json { "keyword": "running shoes for women", "volume": 33100, "cpc": 1.88, "cpc_usd": 1.88, "sd": 64, "pd": 38, "competition": 0.65, "intent": "Commercial, Transactional", "monthly": {"2025-04": 27100, "2025-05": 33100}, "global_breakdown": {"US": 33100, "UK": 8100}, "seed_keyword": "running shoes", "country": "US", "language": "en" } ```` ### Use cases - **SEO content strategy** — find low-difficulty / high-volume opportunities - **Paid search planning** — get CPC + competition before launching campaigns - **Content ideation** — discover questions and modifiers around any topic - **Market entry research** — compare keyword demand across countries - **Competitor briefs** — pull a comprehensive keyword cluster around any brand - **Niche site research** — quickly score the SEO opportunity in any vertical ### Limits - Some long-tail terms have no data — silently dropped (not errored) - Volume figures are estimates from third-party data, not Google Ads Keyword Planner exact-match volumes — use for relative comparisons - A `country=us, limit=500` run can take 60-90 seconds end-to-end ### Related Actors — Free SEO Suite This actor pairs with two other free tools for a complete SEO research workflow: - **[Free Backlink Checker for Website](https://apify.com/s-r/backlinks-checker)** — domain authority + full backlink list for any domain - **[Free URL to Markdown API](https://apify.com/s-r/markdown-anything)** — bulk-extract competitor pages as clean markdown for LLM-driven analysis Use this actor to find ranking opportunities, the backlink checker to score competitor authority, and the markdown converter to bulk-pull their ranking pages for content gap analysis. # Actor input Schema ## `keyword` (type: `string`): The keyword to research (e.g. "running shoes"). Required. ## `country` (type: `string`): ISO 2-letter country code (e.g. nl, us, de, fr). ## `language` (type: `string`): ISO 2-letter language code (e.g. en, nl, de, fr). ## `limit` (type: `integer`): Maximum number of keyword variants to fetch volume for (1-500). ## `max_suggestions` (type: `integer`): Cap autocomplete expansions before volume lookup (0 = use all). ## `min_volume` (type: `integer`): Filter out keywords with monthly search volume below this threshold. ## `concurrency` (type: `integer`): Concurrent requests to the data provider (1-50). Lower if you get rate-limited. ## Actor input object example ```json { "keyword": "coffee maker", "country": "us", "language": "en", "limit": 100, "max_suggestions": 0, "min_volume": 10, "concurrency": 10 } ``` # 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 = { "keyword": "running shoes" }; // Run the Actor and wait for it to finish const run = await client.actor("s-r/google-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 = { "keyword": "running shoes" } # Run the Actor and wait for it to finish run = client.actor("s-r/google-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 '{ "keyword": "running shoes" }' | apify call s-r/google-keywords --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=s-r/google-keywords", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Free Keyword Research Tool for SEO — Volume + CPC", "description": "Free keyword research tool for SEO. Combines Google Autocomplete with monthly search volume, CPC, SEO difficulty, paid difficulty, and search intent classification for any seed keyword in 50+ countries and languages.", "version": "0.1", "x-build-id": "FSkt1qyk6tyksme8h" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/s-r~google-keywords/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-s-r-google-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/s-r~google-keywords/runs": { "post": { "operationId": "runs-sync-s-r-google-keywords", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/s-r~google-keywords/run-sync": { "post": { "operationId": "run-sync-s-r-google-keywords", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "keyword" ], "properties": { "keyword": { "title": "Seed keyword", "type": "string", "description": "The keyword to research (e.g. \"running shoes\"). Required." }, "country": { "title": "Country", "pattern": "^[a-zA-Z]{2}$", "type": "string", "description": "ISO 2-letter country code (e.g. nl, us, de, fr).", "default": "us" }, "language": { "title": "Language", "pattern": "^[a-zA-Z]{2}$", "type": "string", "description": "ISO 2-letter language code (e.g. en, nl, de, fr).", "default": "en" }, "limit": { "title": "Max keywords to return", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of keyword variants to fetch volume for (1-500).", "default": 100 }, "max_suggestions": { "title": "Max autocomplete suggestions", "minimum": 0, "maximum": 500, "type": "integer", "description": "Cap autocomplete expansions before volume lookup (0 = use all).", "default": 0 }, "min_volume": { "title": "Minimum search volume", "minimum": 0, "type": "integer", "description": "Filter out keywords with monthly search volume below this threshold.", "default": 10 }, "concurrency": { "title": "API concurrency", "minimum": 1, "maximum": 50, "type": "integer", "description": "Concurrent requests to the data provider (1-50). Lower if you get rate-limited.", "default": 10 } } }, "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 } } } } } } } } } } ```