# SEO Content Orchestrator - Keyword & SERP Research (`amernas/seo-content-orchestrator`) Actor Automated SEO content research pipeline. Get keyword search volume, CPC, competition data, Google SERP analysis, competitor page crawling, and AI-ready content briefs in one run. Replaces manual workflows across Ahrefs, Surfer SEO, and Clearscope. - **URL**: https://apify.com/amernas/seo-content-orchestrator.md - **Developed by:** [Traffic Architect](https://apify.com/amernas) (community) - **Categories:** AI, SEO tools, Lead generation - **Stats:** 1 total users, 0 monthly users, 0.0% 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 ## SEO Content Orchestrator - Keyword Research, SERP Analysis & Competitor Content Crawler Automated SEO content research pipeline that chains multiple Apify actors to deliver keyword volume data, SERP analysis, competitor page crawling, and actionable content briefs — all in a single run. ### What does SEO Content Orchestrator do? This actor replaces manual SEO research workflows (and expensive tools like AirOps, Surfer SEO, or Clearscope) by orchestrating three Apify Store actors into one automated pipeline: 1. **Keyword Volume & Metrics** — Fetches search volume, CPC, competition level, competition index, and 12-month trend data for every keyword 2. **SERP Analysis** — Scrapes Google search results to extract organic rankings, People Also Ask questions, and related searches 3. **Competitor Content Crawl** — Crawls the top-ranking pages for each keyword and extracts word counts, headings, and content structure 4. **Content Brief Generation** — Aggregates all data into a ready-to-use content brief with target word count, suggested topics, and questions to answer ### Use cases - **Content marketing teams** — Research keywords and generate data-driven content briefs without switching between 5 different SEO tools - **SEO agencies** — Batch-analyze keywords for multiple clients in a single run, export structured reports - **AI content workflows** — Feed the output into Claude, GPT, or any LLM to generate optimized drafts with real SERP data - **Programmatic SEO** — Automate content research at scale for hundreds of keywords - **Competitive analysis** — See exactly what top-ranking pages cover, how long they are, and what questions they answer ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `keywords` | array of strings | *required* | Keywords to research | | `maxKeywords` | integer | 10 | Limit analysis to top N keywords by search volume | | `competitorPagesPerKeyword` | integer | 3 | How many top-ranking pages to crawl per keyword | | `country` | string | `us` | Country code for search results (us, uk, de, etc.) | | `language` | string | `en` | Language code (en, de, fr, etc.) | #### Example input ```json { "keywords": ["web scraping tools", "data extraction API", "browser automation"], "maxKeywords": 5, "competitorPagesPerKeyword": 3, "country": "us", "language": "en" } ```` ### Output Each run produces a single structured report with all pipeline data combined: ```json { "generatedAt": "2026-04-03T11:41:47.937Z", "pipeline": { "keywordVolume": "success", "serpAnalysis": "success", "competitorCrawl": "success" }, "keywords": [ { "keyword": "web scraping tools", "searchVolume": 14800, "cpc": 2.19, "competition": "LOW", "competitionIndex": 16, "monthlySearches": [{"year": 2026, "month": 2, "search_volume": 22200}, ...], "serp": { "organic": [ {"title": "...", "url": "...", "snippet": "...", "position": 1} ], "paa": [{"question": "...", "answer": "..."}], "relatedSearches": ["related term 1", "related term 2"] } } ], "competitorContent": [ {"url": "https://example.com/page", "title": "...", "wordCount": 2500, "headings": ["..."]} ], "contentBrief": { "targetWordCount": 2400, "competitorAvgWordCount": 2100, "paaToAnswer": ["What is web scraping?", "Is web scraping legal?"], "suggestedTopics": ["Getting started", "Best practices", "Tools comparison"] } } ``` ### How it works The actor chains three Apify Store actors using `Actor.call()`: 1. **[Google Keyword Data Extractor](https://apify.com/iskander/google-keyword-search-volume-api)** — Returns search volume, CPC, competition data from Google Ads API 2. **[Google Search Scraper](https://apify.com/apify/google-search-scraper)** — Scrapes Google SERPs for organic results, PAA, related searches 3. **[Website Content Crawler](https://apify.com/apify/website-content-crawler)** — Crawls competitor pages to extract content structure Each step has retry logic with exponential backoff. If any step fails, the pipeline continues with the remaining data — you always get a report. ### Integrations - **MCP Server** — Expose this actor to Claude, GPT, or any AI assistant via [@apify/actors-mcp-server](https://www.npmjs.com/package/@apify/actors-mcp-server) - **Webhooks** — Trigger downstream workflows when the run completes - **API** — Call via Apify API for programmatic access - **Zapier / Make** — Connect to 5,000+ apps ### Related actors - **[AI Brand Monitor](https://apify.com/amernas/ai-brand-monitor)** — Monitor your brand visibility across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews. Pairs with this actor: research keywords here, then track how your brand ranks in AI answers for those same keywords. - **[Company Intelligence Enricher](https://apify.com/amernas/company-intelligence-enricher)** — Enrich company data with Google Knowledge Graph, news, locations, and social links. - **[SERP Feature Tracker](https://apify.com/amernas/serp-feature-tracker)** — Track featured snippets, PAA, and other SERP features over time. ### Pricing This actor calls other Apify Store actors, so costs depend on usage: - Keyword volume: ~$0.005 per keyword - SERP scraping: ~$0.01 per keyword - Content crawling: ~$0.01 per page Typical run for 10 keywords with 3 competitors each: **~$0.50** # Actor input Schema ## `keywords` (type: `array`): Keywords to research (array of strings) ## `maxKeywords` (type: `integer`): Limit analysis to top N keywords by search volume ## `competitorPagesPerKeyword` (type: `integer`): How many top-ranking pages to crawl per keyword ## `country` (type: `string`): Country code for search results (e.g., us, uk, de) ## `language` (type: `string`): Language code (e.g., en, de, fr) ## Actor input object example ```json { "maxKeywords": 10, "competitorPagesPerKeyword": 3, "country": "us", "language": "en" } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("amernas/seo-content-orchestrator").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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("amernas/seo-content-orchestrator").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 amernas/seo-content-orchestrator --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=amernas/seo-content-orchestrator", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SEO Content Orchestrator - Keyword & SERP Research", "description": "Automated SEO content research pipeline. Get keyword search volume, CPC, competition data, Google SERP analysis, competitor page crawling, and AI-ready content briefs in one run. Replaces manual workflows across Ahrefs, Surfer SEO, and Clearscope.", "version": "0.0", "x-build-id": "6bRNX2hBzYmpQClO1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/amernas~seo-content-orchestrator/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-amernas-seo-content-orchestrator", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/amernas~seo-content-orchestrator/runs": { "post": { "operationId": "runs-sync-amernas-seo-content-orchestrator", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/amernas~seo-content-orchestrator/run-sync": { "post": { "operationId": "run-sync-amernas-seo-content-orchestrator", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Keywords", "type": "array", "description": "Keywords to research (array of strings)", "items": { "type": "string" } }, "maxKeywords": { "title": "Max Keywords to Analyze", "minimum": 1, "maximum": 50, "type": "integer", "description": "Limit analysis to top N keywords by search volume", "default": 10 }, "competitorPagesPerKeyword": { "title": "Competitor Pages Per Keyword", "minimum": 1, "maximum": 10, "type": "integer", "description": "How many top-ranking pages to crawl per keyword", "default": 3 }, "country": { "title": "Country", "type": "string", "description": "Country code for search results (e.g., us, uk, de)", "default": "us" }, "language": { "title": "Language", "type": "string", "description": "Language code (e.g., en, de, fr)", "default": "en" } } }, "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 } } } } } } } } } } ```