# Facebook Videos Scraper - Low-costπŸ’²πŸ”₯πŸŽ₯🎬 (`delectable_incubator/facebook-videos-scraper-low-cost`) Actor Scrape Facebook Watch videos by keyword πŸ”πŸŽ₯ with a powerful video scraper. Extract video titles, views, durations, descriptions, upload dates, and video URLs from Facebook Watch search results. Ideal for content research, trend analysis, AI datasets, video monitoring and automated data pipelines πŸ“Š - **URL**: https://apify.com/delectable\_incubator/facebook-videos-scraper-low-cost.md - **Developed by:** [Prime Scrape](https://apify.com/delectable_incubator) (community) - **Categories:** Social media, Videos, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $0.005 / actor start This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 Videos Scraper

--- ## Facebook Videos Scraper πŸŽ₯πŸ“˜πŸš€ The Facebook Videos Scraper is a powerful and scalable Apify Actor designed to extract structured Facebook Watch videos directly from Facebook search results using keywords. It enables content discovery, market research, trend analysis, competitor monitoring, video analytics, AI/ML dataset generation, and structured social media data collection from Facebook Watch. --- ### 🎯 What This Scraper Does Simply provide one or multiple keywords and the scraper handles everything automatically. βœ… Searches Facebook Watch videos by keywords βœ… Supports bulk keyword scraping βœ… Automatically processes video search results βœ… Handles pagination automatically βœ… Applies maxItemsPerKeyword limits βœ… Extracts video metadata and engagement details βœ… Captures upload dates and video durations βœ… Collects thumbnails and direct video URLs βœ… Generates clean and structured datasets βœ… Ready for analytics and automation workflows βœ… Export-ready output format --- ### πŸ“Š Data Extracted #### πŸŽ₯ Video Information | Field | Description | | -------------- | ------------------------------- | | πŸ†” videoId | Unique Facebook video ID | | πŸ“„ title | Video title | | πŸ”— videoUrl | Direct Facebook Watch video URL | | πŸ‘€ views | Video view count | | ⏱ duration | Video duration | | πŸ“… uploadDate | Video upload/publication date | | πŸ“ description | Video description text | | βœ‚οΈ snippet | Related or preview snippet text | | 🌐 platform | Source platform | | πŸ–Ό thumbnail | Video thumbnail URL | | πŸ” keyword | Search keyword used | | πŸ•’ timeFilter | Applied time filter | --- ### πŸ›  How to Use #### 1️⃣ Configure Input Provide one or multiple keywords: ```` { "keywords": \[ "fitness workout", "travel vlog", "cooking recipes" ], "timeFilter": "any", "maxItemsPerKeyword": 20 } ``` #### 2️⃣ Run the Actor β€’ Searches Facebook Watch videos automatically β€’ Processes video search results β€’ Extracts structured video information β€’ Collects views, duration, thumbnails & metadata β€’ Applies maxItemsPerKeyword limits β€’ Stops automatically when limits are reached #### 3️⃣ Export the Dataset Download your results in multiple formats: βœ… JSON βœ… CSV βœ… Excel βœ… XML βœ… HTML --- ### βš™οΈ Input Configuration #### πŸ“₯ Input Example ``` { "keywords": \[ "fitness workout", "travel vlog", "cooking recipes" ], "timeFilter": "month", "maxItemsPerKeyword": 20 } ``` #### Input Fields | Field | Type | Description | | ------------------ | ------- | ----------------------------------------------- | | keywords | array | List of Facebook Watch search keywords | | timeFilter | string | Filter videos by upload time | | maxItemsPerKeyword | integer | Maximum number of videos to collect per keyword | --- ### πŸ“€ Output Example ``` { "videoId": "647023383663540", "title": "Full Body Workout - 25 Minute Standing Cardio | Emma Fitness", "videoUrl": "https://www.facebook.com/watch/?v=647023383663540", "views": "6.5K", "duration": "24:56", "uploadDate": "October 1, 2022", "description": "A 25-minute standing aerobic workout to burn fat and shape your waist.", "snippet": "24:56 Smaller Waist & Flat Belly | 25 Min Standing Aerobic Workout", "platform": "Facebook Watch", "thumbnail": "https://scontent.xx.fbcdn.net/video\_thumbnail.jpg", "keyword": "fitness workout", "timeFilter": "month" } ```` --- ### πŸ“Š Output Explanation | Use Case | Description | | -------------------------- | ------------------------------------------- | | πŸŽ₯ Content Research | Discover trending and niche Facebook videos | | πŸ“ˆ Trend Analysis | Analyze viral video formats and topics | | πŸ“Š Marketing Intelligence | Study engagement and competitors | | πŸ€– AI / ML Datasets | Build structured video datasets | | πŸ”Ž Social Media Monitoring | Track Facebook Watch content | | ⚑ Automation Pipelines | Feed video data into workflows | --- ### 🌍 Why Use This Scraper? πŸŽ₯ Discover Facebook Watch videos at scale πŸ“Š Monitor trending video content πŸ“ˆ Analyze engagement and creators ⚑ Fast and automated extraction πŸ€– Automation-ready structured output πŸ“¦ Bulk keyword scraping support 🧠 Ideal for researchers, marketers, agencies, analysts & developers πŸš€ Scalable for both small and enterprise workloads --- ### πŸ’‘ Keyword Tips πŸ”Ή Broad keywords β†’ larger datasets Examples: fitness, travel, cooking, dogs πŸ”Ή Niche keywords β†’ more targeted results Examples: HIIT cardio beginner, vegan pasta recipe πŸ”Ή Add qualifiers β†’ improve precision Examples: funny dogs 2025, bali travel vlog --- ### ❓ FAQ #### How does this scraper work? The scraper searches Facebook Watch using your keywords and extracts structured video information including titles, URLs, thumbnails, views, upload dates, and descriptions. #### Can I scrape multiple keywords in one run? Yes. You can provide multiple keywords inside the keywords array. #### Does the scraper support time filtering? Yes. You can filter results using: β€’ any β€’ month β€’ year #### Does the scraper collect video thumbnails? Yes. Thumbnail URLs are extracted whenever available. #### Is the data collected live? Yes. Data is extracted directly from Facebook Watch during every run. #### What export formats are supported? JSON, CSV, Excel, XML, and HTML. #### Can I use the extracted data commercially? Yes. The extracted data can be used for analytics, monitoring, research, automation, and commercial applications. #### What happens if the scraper fails? The Actor includes retry mechanisms and automated error handling to improve reliability. #### How long does a run take? Most extractions complete within minutes depending on the number of keywords and requested results. --- ### πŸš€ How to Use 1️⃣ Sign up β€” Create a free Apify account 2️⃣ Find the tool β€” Search for "Facebook Videos Scraper" in the Apify Store 3️⃣ Configure keywords β€” Add one or multiple search keywords 4️⃣ Run it β€” Start the Actor and wait for extraction 5️⃣ Export data β€” Download results in JSON, CSV, Excel, XML, or HTML --- ### ⚠️ Disclaimer This tool is an independent solution and is not affiliated with, endorsed by, or sponsored by Facebook or Meta. --- ### πŸ’Έ Pricing This scraper runs on a **pay-per-result pricing model**. You only pay for successfully extracted records. πŸ’³ **Price:** $2.97 / 1,000 results --- ### Related Actors If you're interested in other Facebook, TikTok, Instagram, YouTube, Lead Generation, or Social Media scraping solutions, explore more tools: (Coming soon) --- ### πŸ“¬ Support ⭐⭐⭐⭐⭐ Leave a 5-star rating if you like this tool For questions, feature requests, custom scrapers, or enterprise requests, feel free to contact us through Apify. --- ### 🌍 PrimeScrape Built for scalable web data extraction & automation. Contact us for custom scraping solutions, enterprise scraping infrastructure, and automation services via Apify. # Actor input Schema ## `KEYWORDS` (type: `array`): List of keywords to search for videos. One keyword per entry. ## `TIME_FILTER` (type: `string`): Filter videos by upload time ## `MAX_ITEMS` (type: `integer`): Maximum number of videos to extract PER KEYWORD ## Actor input object example ```json { "KEYWORDS": [ "fitness", "cooking" ], "TIME_FILTER": "any", "MAX_ITEMS": 10 } ```` # Actor output Schema ## `overview` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "KEYWORDS": [ "fitness", "cooking" ], "TIME_FILTER": "any", "MAX_ITEMS": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("delectable_incubator/facebook-videos-scraper-low-cost").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "KEYWORDS": [ "fitness", "cooking", ], "TIME_FILTER": "any", "MAX_ITEMS": 10, } # Run the Actor and wait for it to finish run = client.actor("delectable_incubator/facebook-videos-scraper-low-cost").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "KEYWORDS": [ "fitness", "cooking" ], "TIME_FILTER": "any", "MAX_ITEMS": 10 }' | apify call delectable_incubator/facebook-videos-scraper-low-cost --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=delectable_incubator/facebook-videos-scraper-low-cost", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Facebook Videos Scraper - Low-costπŸ’²πŸ”₯πŸŽ₯🎬", "description": "Scrape Facebook Watch videos by keyword πŸ”πŸŽ₯ with a powerful video scraper. Extract video titles, views, durations, descriptions, upload dates, and video URLs from Facebook Watch search results. Ideal for content research, trend analysis, AI datasets, video monitoring and automated data pipelines πŸ“Š", "version": "0.0", "x-build-id": "J4ycve9SdnDD4LsvA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/delectable_incubator~facebook-videos-scraper-low-cost/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-delectable_incubator-facebook-videos-scraper-low-cost", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/delectable_incubator~facebook-videos-scraper-low-cost/runs": { "post": { "operationId": "runs-sync-delectable_incubator-facebook-videos-scraper-low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/delectable_incubator~facebook-videos-scraper-low-cost/run-sync": { "post": { "operationId": "run-sync-delectable_incubator-facebook-videos-scraper-low-cost", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "TIME_FILTER", "MAX_ITEMS" ], "properties": { "KEYWORDS": { "title": "Keywords", "type": "array", "description": "List of keywords to search for videos. One keyword per entry.", "items": { "type": "string" } }, "TIME_FILTER": { "title": "Time Filter", "enum": [ "any", "month", "year" ], "type": "string", "description": "Filter videos by upload time", "default": "any" }, "MAX_ITEMS": { "title": "Max Items", "type": "integer", "description": "Maximum number of videos to extract PER KEYWORD", "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 } } } } } } } } } } ```