# SEO Competitor Content Analyzer (`second_coming/seo-content-analyzer`) Actor Analyze competitor web pages for SEO metrics: titles, headings, word count, keywords, topics, readability, and more. - **URL**: https://apify.com/second\_coming/seo-content-analyzer.md - **Developed by:** [Richard P](https://apify.com/second_coming) (community) - **Categories:** SEO tools, Marketing - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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 Competitor Content Analyzer > Analyze competitor web pages for comprehensive SEO content metrics. Built as an [Apify Actor](https://apify.com/actors). ### Features - **Title & Meta Extraction** — Page title, meta description, meta keywords, canonical URL, robots meta - **Heading Analysis** — All headings (h1–h6) extracted with their levels and text - **Word Count & Frequency** — Total word count plus top N most frequent words (stopwords excluded) - **Topic Extraction** — Key topics identified from heading text using significant phrases - **Readability Scoring** — Simple Flesch Reading Ease–style score based on average sentence length and average word length - **Links & Images** — Count of links and images, with up to 50 sample entries - **Deduplication** — Duplicate URLs are automatically deduplicated before analysis - **Graceful Abort** — Handles platform stop signals cleanly - **Webhook Support** — Optional webhook URL notified on completion ### Input | Field | Type | Required | Default | Description | |---|---|---|---|---| | `urls` | `array[string]` | ✅ | — | List of competitor or target URLs to analyze | | `extractTopics` | `boolean` | ❌ | `true` | Extract key topics from heading text | | `analyzeKeywords` | `boolean` | ❌ | `true` | Analyze meta keywords and keyword patterns | | `wordCount` | `boolean` | ❌ | `true` | Compute word count and word frequency | | `maxResults` | `integer` | ❌ | `20` | Max top keywords/words per URL | | `webhookUrl` | `string` | ❌ | — | Optional webhook to notify on completion | #### Example input ```json { "urls": ["https://example.com"], "extractTopics": true, "analyzeKeywords": true, "maxResults": 5 } ```` ### Output Each analyzed URL produces a dataset entry with these fields: | Field | Type | Description | |---|---|---| | `timestamp` | `string` | UTC analysis timestamp | | `url` | `string` | The analyzed URL | | `title` | `string` | HTML `` tag content | | `wordCount` | `integer` | Total words on the page | | `headings` | `array` | All headings (h1–h6) as `{level, text}` objects | | `keywords` | `array` | Extracted keywords (meta + frequent words) | | `topics` | `array` | Key topics identified from headings | | `readabilityScore` | `number` | Readability score (0–100, higher = easier) | | `metaDescription` | `string` | Meta description content | | `wordFrequency` | `array` | Top N frequent words with counts | | `canonicalUrl` | `string` | Canonical URL if set | | `robotsMeta` | `string` | Robots meta tag content | | `metaKeywords` | `array` | Meta keywords if present | | `linksCount` | `integer` | Number of links found | | `imagesCount` | `integer` | Number of images found | | `statusCode` | `integer` | HTTP status code | | `contentType` | `string` | Response content-type | ### Usage #### Local development ```bash ## Install dependencies python3 -m venv .venv source .venv/bin/activate pip install -r requirements.txt ## Run locally apify run --purge ``` #### Deploy to Apify ```bash ## Login (first time only) apify login ## Push and build apify push ``` #### API call ```bash curl -X POST "https://api.apify.com/v2/acts/YOUR_ACTOR_ID/runs" \ -H "Content-Type: application/json" \ -H "Authorization: Bearer YOUR_API_TOKEN" \ -d '{ "urls": ["https://example.com"], "extractTopics": true, "analyzeKeywords": true, "maxResults": 20 }' ``` ### Use cases - **Competitive content audit** — Analyze how competitors structure their pages - **SEO gap analysis** — Identify topics and keywords your content is missing - **Content benchmarking** — Measure word count, readability, and heading usage across competitors - **Technical SEO check** — Verify canonical URLs, meta tags, and robots directives ### Technical stack - [Apify SDK for Python](https://docs.apify.com/sdk/python) - [HTTPX](https://www.python-httpx.org/) — Async HTTP client - [Beautiful Soup](https://www.crummy.com/software/BeautifulSoup/) with `lxml` — HTML parsing ### License MIT # Actor input Schema ## `urls` (type: `array`): List of competitor or target URLs to analyze for SEO content metrics. ## `extractTopics` (type: `boolean`): Whether to extract key topics from heading text. ## `analyzeKeywords` (type: `boolean`): Whether to extract and analyze meta keywords and keyword patterns. ## `wordCount` (type: `boolean`): Whether to compute word count and word frequency analysis. ## `maxResults` (type: `integer`): Maximum number of top keywords/words to return per URL. ## `webhookUrl` (type: `string`): Optional webhook URL to notify when analysis is complete. ## Actor input object example ```json { "urls": [ "https://example.com" ], "extractTopics": true, "analyzeKeywords": true, "wordCount": true, "maxResults": 20 } ``` # 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 '<YOUR_API_TOKEN>' with your token const client = new ApifyClient({ token: '<YOUR_API_TOKEN>', }); // Prepare Actor input const input = { "urls": [ "https://example.com" ], "webhookUrl": "" }; // Run the Actor and wait for it to finish const run = await client.actor("second_coming/seo-content-analyzer").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 '<YOUR_API_TOKEN>' with your token. client = ApifyClient("<YOUR_API_TOKEN>") # Prepare the Actor input run_input = { "urls": ["https://example.com"], "webhookUrl": "", } # Run the Actor and wait for it to finish run = client.actor("second_coming/seo-content-analyzer").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 '{ "urls": [ "https://example.com" ], "webhookUrl": "" }' | apify call second_coming/seo-content-analyzer --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=second_coming/seo-content-analyzer", "--header", "Authorization: Bearer <YOUR_API_TOKEN>" ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "SEO Competitor Content Analyzer", "description": "Analyze competitor web pages for SEO metrics: titles, headings, word count, keywords, topics, readability, and more.", "version": "0.0", "x-build-id": "YfmnuDhwExJWrfuyS" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/second_coming~seo-content-analyzer/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-second_coming-seo-content-analyzer", "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/second_coming~seo-content-analyzer/runs": { "post": { "operationId": "runs-sync-second_coming-seo-content-analyzer", "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/second_coming~seo-content-analyzer/run-sync": { "post": { "operationId": "run-sync-second_coming-seo-content-analyzer", "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": [ "urls" ], "properties": { "urls": { "title": "URLs to analyze", "uniqueItems": true, "type": "array", "description": "List of competitor or target URLs to analyze for SEO content metrics.", "items": { "type": "string" } }, "extractTopics": { "title": "Extract topics from headings", "type": "boolean", "description": "Whether to extract key topics from heading text.", "default": true }, "analyzeKeywords": { "title": "Analyze keywords", "type": "boolean", "description": "Whether to extract and analyze meta keywords and keyword patterns.", "default": true }, "wordCount": { "title": "Compute word count", "type": "boolean", "description": "Whether to compute word count and word frequency analysis.", "default": true }, "maxResults": { "title": "Maximum results per URL", "maximum": 100, "type": "integer", "description": "Maximum number of top keywords/words to return per URL.", "default": 20 }, "webhookUrl": { "title": "Webhook URL (optional)", "type": "string", "description": "Optional webhook URL to notify when analysis is complete." } } }, "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 } } } } } } } } } } ```