# Gohighlevel Blog Parser Spider (`getdataforme/gohighlevel-blog-parser-spider`) Actor This Apify Actor scrapes and extracts comprehensive blog posts from GoHighLevel, capturing titles, descriptions, authors, metadata, and more.... - **URL**: https://apify.com/getdataforme/gohighlevel-blog-parser-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 1,000 results 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 ### Description This Apify Actor scrapes and extracts comprehensive blog posts from GoHighLevel, capturing titles, descriptions, authors, metadata, and more.... --- ## Gohighlevel Blog Parser Spider The Gohighlevel Blog Parser Spider is a powerful Apify Actor designed to scrape and extract blog posts from GoHighLevel's blog platform. It efficiently collects detailed metadata, content summaries, and author information from specified URLs, enabling users to gather insights and data for various analytical purposes. This tool is ideal for businesses and researchers seeking automated, reliable data extraction without manual effort. ### Features - **Comprehensive Data Extraction**: Captures key blog details including titles, descriptions, URLs, publication dates, read times, images, categories, tags, and author info. - **Flexible URL Configuration**: Supports multiple URLs for batch processing, allowing targeted scraping of specific blog endpoints. - **High Reliability**: Built on robust web scraping technology to handle dynamic content and ensure accurate data retrieval. - **Structured Output**: Delivers clean, JSON-formatted results ready for integration into databases, analytics tools, or downstream workflows. - **Performance Optimized**: Processes requests efficiently with minimal overhead, suitable for large-scale data collection. - **Error Handling**: Includes built-in mechanisms to manage network issues, invalid URLs, and parsing errors gracefully. - **Apify Integration**: Seamlessly runs on the Apify platform with easy monitoring, scheduling, and export options. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|---------|----------|-----------------------------------------------------------------------------|---------| | Urls | array | Yes | An array of URLs to scrape blog posts from. Must be valid HTTP/HTTPS URLs. | ["https://backend.leadconnectorhq.com/blogs/posts/list"] | ### Example Usage To run the Actor, provide input parameters in JSON format. Here's an example input: ```json { "Urls": [ "https://backend.leadconnectorhq.com/blogs/posts/list" ] } ```` The Actor will output a JSON array of blog post objects. Example output: ```json [ { "id": "69d8ff3f52d11cf965ba701b", "title": "Did You Know You Can Automate Billing for Subscription Services in HighLevel?", "description": "Learn how HighLevel subscriptions automate billing, create predictable monthly revenue and simplify payment management for your business.", "url": "https://www.gohighlevel.com/post/automate-billing", "url_slug": "automate-billing", "published_at": "2026-04-10T14:00:04.000Z", "updated_at": "2026-04-10T14:00:05.011Z", "read_time_minutes": 1.465, "image_url": "https://assets.cdn.filesafe.space/knES3eSWYIsc5YSZ3YLl/media/69d9025801157e64b3bea569.webp", "image_alt_text": "Automate Billing for Subscription Services in HighLevel", "categories": [ "Payments", "Did You Know?", "Automation" ], "tags": [ "highlevel", "payments", "subscriptions" ], "author_name": "Ryan Howell", "author_image": "https://storage.googleapis.com/msgsndr/knES3eSWYIsc5YSZ3YLl/media/68fb0cae9b2f63348d154d7c.webp", "actor_id": "1N32elMhk5yua1L3e", "run_id": "Bnj3JW9WJIPPiFkrJ" }, { "id": "69d82bc152d11c14e8b24971", "title": "The 15-minute AI responder that follows up with every lead instantly", "description": "If the lead replies, the AI continues the conversation. It answers common questions, qualifies the prospect based on your criteria and books appointments directly into your calendar. All before you or anyone on your team has touched a thing.", "url": "https://www.gohighlevel.com/post/the-15-minute-ai-responder-that-follows-up-with-every-lead-instantly", "url_slug": "the-15-minute-ai-responder-that-follows-up-with-every-lead-instantly", "published_at": "2026-04-09T22:54:02.000Z", "updated_at": "2026-04-09T22:54:02.956Z", "read_time_minutes": 8.965, "image_url": "https://assets.cdn.filesafe.space/knES3eSWYIsc5YSZ3YLl/media/69d82d56d7871cddf7e3c96b.webp", "image_alt_text": "AI. Responder", "categories": [ "AI" ], "tags": [], "author_name": "HighLevel Team", "author_image": "https://storage.googleapis.com/msgsndr/knES3eSWYIsc5YSZ3YLl/media/62b48659c85ecc76fba941f4.jpeg", "actor_id": "1N32elMhk5yua1L3e", "run_id": "Bnj3JW9WJIPPiFkrJ" }, { "id": "69d68b68b4978f45e17ddaad", "title": "HighLevel March 2026 Email Marketing Performance Report", "description": "Discover HighLevel's March 2026 email performance: 1.37B emails sent, 97.47% delivery, and 40.80% open rates, surpassing industry benchmarks for both dedicated and shared domains.", "url": "https://www.gohighlevel.com/post/highlevel-february-2026-email-marketing-performance-report-6033-9007", "url_slug": "highlevel-february-2026-email-marketing-performance-report-6033-9007", "published_at": "2026-04-08T17:22:16.000Z", "updated_at": "2026-04-09T20:58:58.050Z", "read_time_minutes": 2.75, "image_url": "https://assets.cdn.filesafe.space/knES3eSWYIsc5YSZ3YLl/media/69d68fadebf1a608433b7e1d.png", "image_alt_text": "HighLevel March 2026 Email Marketing Performance Report", "categories": [ "Email ", "Email Performance" ], "tags": [ "email deliverability" ], "author_name": "Ryan Howell", "author_image": "https://storage.googleapis.com/msgsndr/knES3eSWYIsc5YSZ3YLl/media/68fb0cae9b2f63348d154d7c.webp", "actor_id": "1N32elMhk5yua1L3e", "run_id": "Bnj3JW9WJIPPiFkrJ" } ] ``` ### Use Cases - **Market Research and Analysis**: Analyze trends in blog content to understand industry shifts and consumer interests. - **Competitive Intelligence**: Monitor competitors' blog updates for insights into their strategies and offerings. - **Content Aggregation**: Build a centralized database of blog posts for content curation and syndication. - **Academic Research**: Collect data for studies on digital marketing, AI, and business automation topics. - **Business Automation**: Integrate extracted data into CRM systems or marketing tools for automated workflows. - **Performance Monitoring**: Track publication frequency and engagement metrics for content strategy optimization. ### Installation and Usage 1. Search for "Gohighlevel Blog Parser Spider" in the Apify Store 2. Click "Try for free" or "Run" 3. Configure input parameters 4. Click "Start" to begin extraction 5. Monitor progress in the log 6. Export results in your preferred format (JSON, CSV, Excel) ### Output Format The Actor outputs a JSON array of objects, each representing a blog post. Key fields include: `id` (unique identifier), `title`, `description`, `url`, `url_slug`, `published_at` and `updated_at` (timestamps), `read_time_minutes`, `image_url` and `image_alt_text`, `categories` and `tags` (arrays), `author_name` and `author_image`, plus `actor_id` and `run_id` for tracking. This structured format ensures easy parsing and integration. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! # Actor input Schema ## `Urls` (type: `array`): The urls for the spider. ## Actor input object example ```json { "Urls": [ "https://backend.leadconnectorhq.com/blogs/posts/list" ] } ``` # 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("getdataforme/gohighlevel-blog-parser-spider").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("getdataforme/gohighlevel-blog-parser-spider").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 getdataforme/gohighlevel-blog-parser-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/gohighlevel-blog-parser-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Gohighlevel Blog Parser Spider", "description": "This Apify Actor scrapes and extracts comprehensive blog posts from GoHighLevel, capturing titles, descriptions, authors, metadata, and more....", "version": "0.0", "x-build-id": "cKz5tgzgHrAeiuuka" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~gohighlevel-blog-parser-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-gohighlevel-blog-parser-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~gohighlevel-blog-parser-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-gohighlevel-blog-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~gohighlevel-blog-parser-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-gohighlevel-blog-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "default": [ "https://backend.leadconnectorhq.com/blogs/posts/list" ], "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```