# Meta Ads Library Scraper - Facebook & Instagram Ads No Login (`groupoject/meta-ads-library-scraper-no-login`) Actor Scrape public Meta Ad Library ads from Facebook and Instagram without a Meta API token. Extract ad copy, page names, dates, landing domains, CTAs, links, and competitor ad examples. - **URL**: https://apify.com/groupoject/meta-ads-library-scraper-no-login.md - **Developed by:** [Group Oject](https://apify.com/groupoject) (community) - **Categories:** Automation, E-commerce, Social media - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 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 ## Meta Ads Library Scraper - Facebook & Instagram Ads No Login Scrape public ads from Meta Ad Library without creating a Meta app, passing app review, or pasting an access token. Use it to monitor competitor ads, collect Facebook and Instagram ad examples, research landing pages, track ad copy, and export public ad cards from Meta Ad Library to JSON, CSV, Excel, or your API workflow. ### What You Get - Public Meta Ad Library ads by keyword, advertiser Page ID, or Ad Library URL - Ad Library ID and direct snapshot URL - Advertiser/page name - Ad copy and creative text visible on the public card - Landing domain, link title, description, and CTA when visible - Active/inactive status - Start and stop dates when visible - Country, query, and source search URL - Flags for multiple versions and EU transparency ### Why This Actor Most Meta Ad Library API workflows require a Meta developer app and access token. That is slow for marketers, agencies, ecommerce teams, and competitor researchers who just want public ad examples. This Actor uses the public Meta Ad Library website in a real browser. Paste a keyword, Facebook Page ID, or Ad Library URL and run. ### Example Use Cases - Find active Facebook and Instagram ads for a brand - Track competitor messaging and offers - Collect ecommerce ad examples for products or categories - Monitor SaaS, agency, local business, and political ad campaigns - Build a swipe file of landing domains, hooks, CTAs, and creative angles - Feed public ad examples into AI research, dashboards, or MCP workflows ### Input ```json { "searchTerms": ["nike", "crm software", "meal delivery"], "countries": ["US"], "activeStatus": "ACTIVE", "adType": "ALL", "mediaType": "ALL", "sortMode": "total_impressions", "maxAdsPerQuery": 100, "maxTotalAds": 100, "dedupe": true } ```` You can also pass: - `pageIds` for advertiser-specific scraping - `adLibraryUrls` for exact searches copied from Meta Ad Library - multiple country codes such as `US`, `GB`, `CA`, `AU`, `DE` ### Output Example ```json { "query": "nike", "queryType": "search_term", "country": "US", "adArchiveId": "1869276447125570", "adSnapshotUrl": "https://www.facebook.com/ads/library/?id=1869276447125570", "activeStatus": "ACTIVE", "pageName": "Nike", "adCreativeBody": "Get the gear that goes hard on and off the field.", "adCreativeLinkCaption": "nike.com", "cta": "Shop Now", "adDeliveryStartTime": "2026-06-20T00:00:00.000Z", "hasMultipleVersions": true, "hasEuTransparency": false, "fetchedAt": "2026-06-27T12:00:00.000Z" } ``` ### Notes and Limits This Actor extracts data visible on public Meta Ad Library result cards. Some fields, such as spend, impressions, demographics, and detailed targeting, may only be visible for special transparency categories or through Meta's official API. For the highest reliability: - Start with 1-5 search terms - Use `ACTIVE` ads first - Keep the default `maxTotalAds` at 100 for small test runs - Increase `maxTotalAds` only when you are ready to export more ads - Use residential proxy if Meta blocks requests in your environment ### Pricing Suggestion Recommended Store pricing: **$1.00 per 500 ads**. In Apify monetization, set the result event price to **$0.002 per result**. That displays as $2.00 / 1,000 ads in some Apify UI views, but the buyer-facing positioning can be $1 per 500 ads. This is business-intelligence data for agencies, marketers, ecommerce teams, and SaaS operators. The no-token workflow saves users setup time, which justifies pricing above generic scraping actors. # Actor input Schema ## `searchTerms` (type: `array`): Keywords or brands to search in the public Meta Ad Library. ## `searchTermsText` (type: `string`): Paste one search term per line or comma-separated. ## `pageIds` (type: `array`): Optional Facebook Page IDs to scrape ads from a specific advertiser. ## `adLibraryUrls` (type: `array`): Optional full Meta Ad Library search URLs. Use this when you already configured filters in the browser. ## `countries` (type: `array`): Country codes to search, such as US, GB, CA, AU, DE. ## `adType` (type: `string`): All ads is best for competitor research. Political and issue ads can show more transparency fields in Meta. ## `activeStatus` (type: `string`): Choose active, inactive, or all ads. ## `mediaType` (type: `string`): Filter results by creative media type. ## `sortMode` (type: `string`): Sort by impressions where Meta supports it, or use relevancy. ## `maxAdsPerQuery` (type: `integer`): Maximum ads to collect per keyword, page ID, or Ad Library URL. ## `maxTotalAds` (type: `integer`): Maximum ads to output across the whole run. Default is capped at 100 ads so test runs stay small. ## `maxQueries` (type: `integer`): Maximum search targets to process. ## `dedupe` (type: `boolean`): Remove duplicate Library IDs across all queries and countries. ## `scrollDelayMs` (type: `integer`): Delay after each scroll while new ads load. ## `maxScrolls` (type: `integer`): Maximum scroll attempts per query. ## `proxyConfiguration` (type: `object`): Optional proxy. Use residential proxy if Meta blocks requests in your environment. ## `headless` (type: `boolean`): Run Chrome in headless mode. ## `debugMode` (type: `boolean`): Verbose logging. ## Actor input object example ```json { "searchTerms": [ "nike", "openai", "crm software" ], "countries": [ "US" ], "adType": "ALL", "activeStatus": "ACTIVE", "mediaType": "ALL", "sortMode": "total_impressions", "maxAdsPerQuery": 100, "maxTotalAds": 100, "maxQueries": 20, "dedupe": true, "scrollDelayMs": 1800, "maxScrolls": 20, "proxyConfiguration": { "useApifyProxy": false }, "headless": true, "debugMode": false } ``` # Actor output Schema ## `ads` (type: `string`): One row per public ad card from Meta Ad Library. ## `adsByPage` (type: `string`): Ads grouped by advertiser/page. ## `summary` (type: `string`): Totals, top pages, and warnings. ## `errors` (type: `string`): Queries that failed. # 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 = { "searchTerms": [ "nike", "openai", "crm software" ], "countries": [ "US" ] }; // Run the Actor and wait for it to finish const run = await client.actor("groupoject/meta-ads-library-scraper-no-login").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 = { "searchTerms": [ "nike", "openai", "crm software", ], "countries": ["US"], } # Run the Actor and wait for it to finish run = client.actor("groupoject/meta-ads-library-scraper-no-login").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 '{ "searchTerms": [ "nike", "openai", "crm software" ], "countries": [ "US" ] }' | apify call groupoject/meta-ads-library-scraper-no-login --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=groupoject/meta-ads-library-scraper-no-login", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Meta Ads Library Scraper - Facebook & Instagram Ads No Login", "description": "Scrape public Meta Ad Library ads from Facebook and Instagram without a Meta API token. Extract ad copy, page names, dates, landing domains, CTAs, links, and competitor ad examples.", "version": "1.0", "x-build-id": "ivOYJbJcPGvPbejYw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/groupoject~meta-ads-library-scraper-no-login/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-groupoject-meta-ads-library-scraper-no-login", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/groupoject~meta-ads-library-scraper-no-login/runs": { "post": { "operationId": "runs-sync-groupoject-meta-ads-library-scraper-no-login", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/groupoject~meta-ads-library-scraper-no-login/run-sync": { "post": { "operationId": "run-sync-groupoject-meta-ads-library-scraper-no-login", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchTerms": { "title": "Search terms", "uniqueItems": true, "type": "array", "description": "Keywords or brands to search in the public Meta Ad Library.", "items": { "type": "string" } }, "searchTermsText": { "title": "Bulk search terms", "type": "string", "description": "Paste one search term per line or comma-separated." }, "pageIds": { "title": "Facebook page IDs", "uniqueItems": true, "type": "array", "description": "Optional Facebook Page IDs to scrape ads from a specific advertiser.", "items": { "type": "string" } }, "adLibraryUrls": { "title": "Meta Ad Library URLs", "uniqueItems": true, "type": "array", "description": "Optional full Meta Ad Library search URLs. Use this when you already configured filters in the browser.", "items": { "type": "string" } }, "countries": { "title": "Countries", "type": "array", "description": "Country codes to search, such as US, GB, CA, AU, DE.", "default": [ "US" ], "items": { "type": "string" } }, "adType": { "title": "Ad type", "enum": [ "ALL", "POLITICAL_AND_ISSUE_ADS" ], "type": "string", "description": "All ads is best for competitor research. Political and issue ads can show more transparency fields in Meta.", "default": "ALL" }, "activeStatus": { "title": "Active status", "enum": [ "ACTIVE", "INACTIVE", "ALL" ], "type": "string", "description": "Choose active, inactive, or all ads.", "default": "ACTIVE" }, "mediaType": { "title": "Media type", "enum": [ "ALL", "IMAGE", "VIDEO" ], "type": "string", "description": "Filter results by creative media type.", "default": "ALL" }, "sortMode": { "title": "Sort by", "enum": [ "total_impressions", "relevancy" ], "type": "string", "description": "Sort by impressions where Meta supports it, or use relevancy.", "default": "total_impressions" }, "maxAdsPerQuery": { "title": "Max ads per query", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum ads to collect per keyword, page ID, or Ad Library URL.", "default": 100 }, "maxTotalAds": { "title": "Max total ads", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum ads to output across the whole run. Default is capped at 100 ads so test runs stay small.", "default": 100 }, "maxQueries": { "title": "Max queries", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum search targets to process.", "default": 20 }, "dedupe": { "title": "Deduplicate ads", "type": "boolean", "description": "Remove duplicate Library IDs across all queries and countries.", "default": true }, "scrollDelayMs": { "title": "Scroll delay (ms)", "minimum": 500, "maximum": 10000, "type": "integer", "description": "Delay after each scroll while new ads load.", "default": 1800 }, "maxScrolls": { "title": "Max scrolls", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum scroll attempts per query.", "default": 20 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Optional proxy. Use residential proxy if Meta blocks requests in your environment.", "default": { "useApifyProxy": false } }, "headless": { "title": "Headless browser", "type": "boolean", "description": "Run Chrome in headless mode.", "default": true }, "debugMode": { "title": "Debug mode", "type": "boolean", "description": "Verbose logging.", "default": false } } }, "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 } } } } } } } } } } ```