# Facebook Comments Scraper | Webhook Support (`devninja/facebook-comments-scraper-webhook-support`) Actor This Apify actor is designed for businesses, teams, and individuals—supporting video URLs, post URLs, photo URLs, and reels—without the hassle of manual scraping or complex setups, making it perfect for analyzing conversations, monitoring engagement, and gathering insights from Facebook. - **URL**: https://apify.com/devninja/facebook-comments-scraper-webhook-support.md - **Developed by:** [Devinja](https://apify.com/devninja) (community) - **Categories:** E-commerce, Social media, Integrations - **Stats:** 47 total users, 2 monthly users, 0.0% runs succeeded, 5 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing Pay per event 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 ## Facebook Comments Scraper – Webhook Support This Apify actor is ideal for business, teams and individuals looking to **analyze conversations**, **monitor engagement**, or **gather insights** from Facebook without dealing with manual scraping or complex setups. --- ### Supported Content Types Unlike other tools, this actor supports extracting comments from **all major Facebook content types**: - **Posts/Stories**: `https://www.facebook.com/story.php?story_fbid=xxxx&id=xxxx&_rdr` - **Reels**: `https://web.facebook.com/reel/xxxxxx` - **Photos**: `https://web.facebook.com/photo/?fbid=xxxx&set=xxxxx` - **Videos**: `https://web.facebook.com/watch?v=xxxxx` --- ### Compatible With This actor is designed to work seamlessly alongside: - **[Facebook Post Scraper](https://console.apify.com/actors/RJhD7EVn1ClNidtKk/)** Extracts detailed data from public Facebook posts (e.g. post text, media, reactions). - **[Facebook Post Scraper: Webhook Support](https://console.apify.com/actors/P1ftsGcNuXmD4HHHY/source)** Includes webhook integration to send post data automatically to your API. Use all three actors together for **complete Facebook post + comment analysis** with minimal effort. --- ### Key Benefits - **Supports all content types** — posts, photos, reels, and videos - **Webhook-ready** — automatically sends data to your endpoint - **Structured results** with author info, timestamps, reactions, and more - **Processes multiple post URLs at once** --- ### How It Works 1. **Input** your list of Facebook URLs (posts, photos, reels, or videos) 2. (Optional) Provide a webhook URL to receive the output automatically 3. Run the actor — it crawls each URL, extracts comment data, and sends it to you --- # Actor input Schema ## `startUrls` (type: `array`): Array of Facebook either POST, VIDEO, REEL and PHOTO URLs to extract comments from ## `resultsLimit` (type: `integer`): Maximum number of comments to extract per url (1-1000) ## `viewOption` (type: `string`): Comment sorting/filtering option ## `webhook_url` (type: `string`): URL to submit crawling results after completion (optional) ## `webhook_token` (type: `string`): Bearer token for webhook authentication (optional but recommended if using webhook). It can be any custom string (e.g., 'my-secret-token-123'). ## `webhook_method` (type: `string`): HTTP method to use for webhook submission ## Actor input object example ```json { "startUrls": [ { "url": "https://www.facebook.com/photo/?fbid=1310367533784524&set=a.743777527110197", "method": "GET" } ], "resultsLimit": 10, "viewOption": "RANKED_UNFILTERED", "webhook_url": "https://your-api.com/webhook/facebook-comments", "webhook_method": "POST" } ```` # 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("devninja/facebook-comments-scraper-webhook-support").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("devninja/facebook-comments-scraper-webhook-support").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 devninja/facebook-comments-scraper-webhook-support --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=devninja/facebook-comments-scraper-webhook-support", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Facebook Comments Scraper | Webhook Support", "description": "This Apify actor is designed for businesses, teams, and individuals—supporting video URLs, post URLs, photo URLs, and reels—without the hassle of manual scraping or complex setups, making it perfect for analyzing conversations, monitoring engagement, and gathering insights from Facebook.", "version": "1.0", "x-build-id": "JFS0VrNYlbnVytsL0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/devninja~facebook-comments-scraper-webhook-support/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-devninja-facebook-comments-scraper-webhook-support", "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/devninja~facebook-comments-scraper-webhook-support/runs": { "post": { "operationId": "runs-sync-devninja-facebook-comments-scraper-webhook-support", "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/devninja~facebook-comments-scraper-webhook-support/run-sync": { "post": { "operationId": "run-sync-devninja-facebook-comments-scraper-webhook-support", "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": [ "startUrls" ], "properties": { "startUrls": { "title": "Post URL's", "minItems": 1, "maxItems": 100, "type": "array", "description": "Array of Facebook either POST, VIDEO, REEL and PHOTO URLs to extract comments from", "items": { "type": "object", "properties": { "url": { "title": "URL", "type": "string", "description": "Facebook post URL", "pattern": "^https://(www\\.|web\\.|m\\.|mobile\\.|mbasic\\.)?facebook\\.com/" }, "method": { "title": "Method", "type": "string", "description": "HTTP method (always GET for Facebook posts)" } }, "required": [ "url" ], "additionalProperties": false }, "default": [ { "url": "https://www.facebook.com/photo/?fbid=1310367533784524&set=a.743777527110197", "method": "GET" } ] }, "resultsLimit": { "title": "Results Limit", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of comments to extract per url (1-1000)", "default": 10 }, "viewOption": { "title": "View Option", "enum": [ "RANKED_UNFILTERED", "CHRONOLOGICAL", "RECENT_ACTIVITY" ], "type": "string", "description": "Comment sorting/filtering option", "default": "RANKED_UNFILTERED" }, "webhook_url": { "title": "Webhook URL", "type": "string", "description": "URL to submit crawling results after completion (optional)", "default": "" }, "webhook_token": { "title": "Webhook Authentication Token", "type": "string", "description": "Bearer token for webhook authentication (optional but recommended if using webhook). It can be any custom string (e.g., 'my-secret-token-123')." }, "webhook_method": { "title": "Webhook HTTP Method", "enum": [ "POST", "PUT" ], "type": "string", "description": "HTTP method to use for webhook submission", "default": "POST" } } }, "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 } } } } } } } } } } ```