# Meta | Facebook Ads Library Scraper - RealFast (`magnolia_yont/meta-facebook-ads-library-scraper-realfast`) Actor $0.29 per 1,000 ads. Real fast. Real cheap. Real complete. Scrape the Facebook (Meta) Ads Library β€” creative, copy, CTA, reach & more, streamed to your dataset in minutes. Proxy included, zero setup, from $0.29 per 1,000 ads. - **URL**: https://apify.com/magnolia\_yont/meta-facebook-ads-library-scraper-realfast.md - **Developed by:** [Roger Vance](https://apify.com/magnolia_yont) (community) - **Categories:** Social media, E-commerce, Lead generation - **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.29 / 1,000 ads scrapeds 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Meta | Facebook Ads Library Scraper - RealFast **Real fast. Real cheap. Real complete. Turn any Facebook (Meta) Ads Library search into clean, structured data in minutes β€” every creative, every headline, every call-to-action β€” for just $0.29 per 1,000 ads. Proxy included. Nothing to set up.** Researching competitors, building a swipe file, or tracking a brand's entire ad strategy? Paste one search URL and get a complete, spreadsheet-ready export of live and past ads in minutes β€” ready for CSV, Excel, JSON, or API. --- ### Why teams choose it - πŸ’° **Unbeatable net price** β€” **$0.29 per 1,000 ads**, the lowest real rate on the market, with proxy and compute already inside. The price you see is the whole bill. - 🎯 **The complete ad, not just the image** β€” copy, call-to-action, format, page details, run dates, platforms, reach & impression estimates, regional disclosures, and the full original snapshot. - ⚑ **Fast** β€” results stream into your dataset as they're collected, so most searches finish in minutes. - πŸ›‘οΈ **Never lose a run** β€” every ad is saved the moment it's found. If a run stops early, everything gathered so far is already yours. - πŸ”Œ **Zero setup** β€” no proxy to buy, no accounts to connect, no settings to tune. Paste a URL and go. - πŸ’³ **Pay only for what you receive** β€” billed per ad delivered to your dataset. No ads, no charge. --- ### What you can do with it - πŸ” **Competitor research** β€” see every ad a brand or page is running right now, at a glance. - 🎨 **Creative swipe files** β€” collect winning hooks, headlines, and ad formats for inspiration. - πŸ“Š **Market & trend intelligence** β€” track how an entire industry advertises across countries and over time. - πŸ“ˆ **Campaign monitoring** β€” catch competitors the moment they launch, pause, or refresh their creative. - 🧲 **Prospecting** β€” find brands actively investing in advertising and reach out with proof in hand. --- ### What you get for every ad | Category | Details | |---|---| | **Creative** | Images, videos, and carousel cards, with direct media links | | **Messaging** | Full ad copy, call-to-action text and type, and display format | | **Advertiser** | Page name, page link, website, and page details | | **Timing & status** | Start/end dates and whether the ad is currently active | | **Distribution** | The platforms each ad runs on | | **Performance signals** | Reach and impression estimates, and regional disclosures where public | | **Everything else** | The complete original snapshot, so no detail is ever left behind | No duplicates, no half-records β€” just clean, ready-to-use ad data. --- ### Pricing **Simple and transparent β€” you only pay for the ads you actually get.** | | Price | |---|---| | **Ads delivered** | **$0.29 per 1,000 ads** | | **Proxy** | Included β€” about **$0.02 per 1,000 ads** | | **All-in** | **β‰ˆ $0.31 per 1,000 ads** | This is the **net price** β€” compute and proxy are already inside these numbers. Nothing extra lands on your Apify bill. Every ad is written to your dataset **before** it's charged, so you're never billed for data you didn't receive. --- ### Why pay $10–15 per 1,000 for the same public data? Every Facebook Ad Library scraper β€” including the "premium" ones β€” reads from the exact same public source: **Meta's Ad Library**. No scraper on any platform can extract more than what Meta publicly discloses. The real difference is what you pay for it. | | "Premium" Meta ad scrapers | **This scraper** | |---|---|---| | **Price per 1,000 ads** | $10–15 | **$0.29** (β‰ˆ $0.31 all-in, proxy included) | | **Data source** | Meta Ad Library (public) | Meta Ad Library (public) β€” the same one | | **Creative, copy, CTA, media** | βœ… | βœ… | | **Reach / impressions / spend** | Only where Meta discloses them | Only where Meta discloses them β€” any scraper promising these on *every* ad is overselling | | **Full original snapshot** | Varies | βœ… Always included | | **Proxy** | Often billed separately | Included | | **Meta developer app / API token** | None needed | None needed | Same source. Same fields. Same limits. **Real difference: the price.** #### And watch out for the other trick: teaser prices Some scrapers advertise rock-bottom rates like *"$0.30 per 1,000 ads"* β€” but that number quietly excludes the per-result fees, the compute, or the residential proxy that get **billed to your Apify account on top**. The real total only shows up on your invoice afterwards. We quote one **net price** instead: **β‰ˆ $0.31 per 1,000 ads, all-in.** No platform usage on top, no proxy surprise, no fine print. Our *real* total is what teaser pricing only pretends to be. --- ### Get started in 3 steps 1. Open the **Meta Ads Library**, run your search (keyword, country, date range β€” any filters you like), and copy the URL from your browser. 2. Paste it into **`searchUrl`**, and optionally set how many ads you want with **`maxAds`**. 3. **Run.** Your structured ad data lands in the dataset, ready to export to CSV, Excel, JSON, or pull via API. #### Input | Field | Type | Required | Description | |---|---|---|---| | `searchUrl` | string | βœ… | A Meta Ads Library search URL (`https://www.facebook.com/ads/library/...`). Include any filters β€” keyword, country, date range, and more. | | `maxAds` | integer | | How many ads to collect (0–10000). Default `1000`. | | `datasetId` | string | | Where to store results. Defaults to the run's own dataset. | ```json { "searchUrl": "https://www.facebook.com/ads/library/?active_status=active&ad_type=all&country=US&q=nike&search_type=keyword_unordered", "maxAds": 1000 } ```` *** ### Output Results are written **progressively as they're collected**, so your data is growing while the run is still going. Each dataset record holds a batch of ads: ```json { "timestamp": "2026-07-17T02:00:00.000Z", "total": 10, "success": 10, "failed": 0, "results": [ { "FB AD Link": "https://www.facebook.com/ads/library/?id=1234567890123456", "FB Link": "https://www.facebook.com/examplebrand/", "Company Name": "Example Brand", "Website": "examplebrand.com", "ad_archive_id": "1234567890123456", "page_id": "100000000000000", "page_name": "Example Brand", "is_active": true, "categories": ["UNKNOWN"], "publisher_platform": ["FACEBOOK", "INSTAGRAM", "AUDIENCE_NETWORK", "MESSENGER"], "start_date": 1766563200, "end_date": 1766649600, "reach_estimate": null, "spend": null, "currency": "", "impressions_with_index": { "impressions_text": null, "impressions_index": -1 }, "regional_regulation_data": { "finserv": { "is_deemed_finserv": false } }, "snapshot": { "page_name": "Example Brand", "page_like_count": 12000, "cta_text": "Shop Now", "cta_type": "SHOP_NOW", "display_format": "VIDEO", "body": { "text": "Your ad body text appears here..." }, "cards": [], "images": [{ "original_image_url": "https://...", "resized_image_url": "https://..." }], "videos": [{ "video_sd_url": "https://...", "video_preview_image_url": "https://..." }] } } ] } ``` Each record carries `timestamp`, `total`, `success`, `failed`, and `results` (the batch of ads). To collect every ad, iterate the `results` array across the dataset records. Every ad object includes handy quick-links (`FB AD Link`, `FB Link`, `Company Name`, `Website`), the ad's public data (`ad_archive_id`, `page_id`, `publisher_platform`, `start_date`/`end_date`, `reach_estimate`, `impressions_with_index`, `regional_regulation_data`, and more), and a complete `snapshot` with the creative, copy, CTA, page details, and media (`images`, `videos`, `cards`). *** ### Good to know - Dates are Unix timestamps (in seconds). - `reach_estimate`, `spend`, and `impressions` appear only when Meta makes them public for that ad and region. - For the fastest, most focused runs, use a specific `searchUrl` β€” a keyword plus a country and date range works best. *** ### FAQ **Is it legal to scrape the Meta Ad Library?** The Ad Library is Meta's own public transparency product. Using it for research, competitive intelligence, journalism, and compliance monitoring is widely accepted. You remain responsible for complying with Meta's Terms of Service and your local data laws. **Why don't all ads have spend and impressions?** Because Meta only discloses them for political & issue ads, plus reach data under EU (DSA) transparency rules. Regular commercial ads simply don't carry those numbers β€” from **any** scraper, at **any** price. This scraper returns them honestly whenever Meta publishes them (`reach_estimate`, `spend`, `impressions_with_index`). **Can I search by keyword, Page ID, country, or date range?** Yes β€” run any search in the [Ad Library](https://www.facebook.com/ads/library) (keyword, page, country, date range, ad type, platform…), copy the URL from your browser, and paste it into `searchUrl`. Every filter the Ad Library supports, this scraper honors. **Do I need a Meta developer app or API token?** No. No Graph API, no app review, no token lifecycle. Paste a URL and run. **What export formats are supported?** Everything Apify datasets offer: CSV, Excel, JSON, XML, HTML β€” or pull results programmatically via the Apify API. **What happens if a run stops early?** Nothing is lost. Every ad is saved to your dataset the moment it's collected, and you're only charged for ads actually delivered. **Why do some scrapers advertise "$0.30 per 1,000" yet cost several times more?** Because the advertised number often covers only part of the bill β€” per-result event fees, compute, or residential proxy are charged to **your** account separately. Always check what actually lands on your invoice. Our β‰ˆ $0.31 per 1,000 is the **net, all-in price**: proxy and compute included, nothing billed on top. *** **Ready to see what your competitors are really running?** Paste a search URL and go. πŸš€ # Actor input Schema ## `searchUrl` (type: `string`): A Facebook (Meta) Ads Library search URL. Open the Ads Library, run your search with any filters (keyword, country, date range, etc.), and paste the URL from your browser. ## `maxAds` (type: `integer`): Maximum number of ads to collect. Set to 0 for unlimited (not recommended). ## `datasetId` (type: `string`): Apify dataset ID to store results. Leave empty to use the default run dataset. ## Actor input object example ```json { "searchUrl": "https://www.facebook.com/ads/library/?active_status=active&ad_type=all&country=US&q=nike&search_type=keyword_unordered", "maxAds": 100, "datasetId": "n2cbYwFAdOlNoD9JJ" } ``` # Actor output Schema ## `results` (type: `string`): Items of the default dataset. Each item wraps one page of scraped ads in its results array. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchUrl": "https://www.facebook.com/ads/library/?active_status=active&ad_type=all&country=US&q=nike&search_type=keyword_unordered", "maxAds": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("magnolia_yont/meta-facebook-ads-library-scraper-realfast").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${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 = { "searchUrl": "https://www.facebook.com/ads/library/?active_status=active&ad_type=all&country=US&q=nike&search_type=keyword_unordered", "maxAds": 100, } # Run the Actor and wait for it to finish run = client.actor("magnolia_yont/meta-facebook-ads-library-scraper-realfast").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 '{ "searchUrl": "https://www.facebook.com/ads/library/?active_status=active&ad_type=all&country=US&q=nike&search_type=keyword_unordered", "maxAds": 100 }' | apify call magnolia_yont/meta-facebook-ads-library-scraper-realfast --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=magnolia_yont/meta-facebook-ads-library-scraper-realfast", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Meta | Facebook Ads Library Scraper - RealFast", "description": "$0.29 per 1,000 ads. Real fast. Real cheap. Real complete. Scrape the Facebook (Meta) Ads Library β€” creative, copy, CTA, reach & more,\n streamed to your dataset in minutes. Proxy included, zero setup, from $0.29 per 1,000 ads.", "version": "1.0", "x-build-id": "qn5VxcSGzC2xTtAE1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/magnolia_yont~meta-facebook-ads-library-scraper-realfast/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-magnolia_yont-meta-facebook-ads-library-scraper-realfast", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/magnolia_yont~meta-facebook-ads-library-scraper-realfast/runs": { "post": { "operationId": "runs-sync-magnolia_yont-meta-facebook-ads-library-scraper-realfast", "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/magnolia_yont~meta-facebook-ads-library-scraper-realfast/run-sync": { "post": { "operationId": "run-sync-magnolia_yont-meta-facebook-ads-library-scraper-realfast", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "searchUrl" ], "properties": { "searchUrl": { "title": "Search URL", "pattern": "^https?://www\\.facebook\\.com/ads/library/.*$", "type": "string", "description": "A Facebook (Meta) Ads Library search URL. Open the Ads Library, run your search with any filters (keyword, country, date range, etc.), and paste the URL from your browser." }, "maxAds": { "title": "Maximum Ads", "minimum": 0, "maximum": 10000, "type": "integer", "description": "Maximum number of ads to collect. Set to 0 for unlimited (not recommended).", "default": 1000 }, "datasetId": { "title": "Dataset ID", "pattern": "^[a-zA-Z0-9_/.-]{0,80}$", "type": "string", "description": "Apify dataset ID to store results. Leave empty to use the default run dataset." } } }, "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 } } } } } } } } } } ```