# Facebook Group Posts Scraper (No Login Required) (`iron-crawler/facebook-group-posts`) Actor Scrape Facebook group posts at lightning speed. Zero-config API pipeline exports bulk data in JSON/CSV for instant social media intelligence and competitive analysis. - **URL**: https://apify.com/iron-crawler/facebook-group-posts.md - **Developed by:** [Iron Crawler](https://apify.com/iron-crawler) (community) - **Categories:** Social media, Automation, Developer tools - **Stats:** 33 total users, 2 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 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. 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 Group Posts Scraper (No Login Required) ### What does Facebook Group Posts Scraper (No Login Required) do? This tool extracts comprehensive data from Facebook groups without requiring authentication or login credentials. Built with a cookieless architecture, the scraper eliminates the complexity of managing sessions, cookies, or account credentials while delivering reliable access to public group content. Simply provide a group ID, and the tool handles the rest, making it ideal for researchers, marketers, and analysts who need consistent data access without the overhead of account management. **Key Features:** - **No login required**: Scrape Facebook group posts without authentication barriers - **Comprehensive post data**: Extract text content, author information, timestamps, and engagement metrics - **Media attachment support**: Capture URLs for images and other attachments shared in posts - **Group metadata**: Access member counts and group-level statistics - **Multiple export formats**: Download data in JSON, CSV, or Excel formats - **Flexible input**: Simple group ID-based configuration - **Scalable extraction**: Process multiple groups or posts efficiently ### Why scrape Facebook group posts? Social media community managers need to extract group posts from various platforms to analyze engagement trends, content strategies, and audience sentiment for competitive intelligence. Facebook groups represent concentrated communities where authentic conversations happen, making them invaluable sources of market insights, customer feedback, and emerging trends. By systematically collecting and analyzing group post data, organizations can make data-driven decisions about content strategy, product development, and community engagement. **Primary Use Cases:** - **Competitive Intelligence**: Monitor competitor communities to understand their content strategies, engagement patterns, and audience responses. Track what topics resonate, which post formats drive interaction, and how competitors position their messaging. - **Lead Generation**: Identify potential customers by analyzing group discussions, questions, and pain points. Extract contact information and engagement signals from active community members who demonstrate interest in relevant topics. - **Trend Analysis & Market Research**: Discover emerging trends, common challenges, and sentiment patterns within target communities. Analyze conversation themes, frequently discussed topics, and community concerns to inform product roadmaps and marketing campaigns. ### How to scrape Facebook group posts using this tool? **Step 1: Find the Group ID** Navigate to the Facebook group you want to scrape. The group ID is typically found in the URL (e.g., `facebook.com/groups/1439220986320043`) or can be extracted using Facebook's page transparency tools. Copy this numeric identifier. **Step 2: Configure the input parameters** Enter the group ID into the scraper's input field. You can optionally configure the number of posts to extract. Note that **1 page ≈ 50 items**, so plan your extraction volume accordingly based on your analysis needs and available resources. **Step 3: Run and Download** Start the scraper and wait for the extraction to complete. Once finished, download your data in your preferred format (JSON for technical integration, CSV for spreadsheet analysis, or Excel for business reporting). The data is immediately ready for analysis or import into your preferred tools. ### What are the input parameters? | Field | Type | Description | |-------|------|-------------| | `groupId` | String | The unique numeric identifier for the Facebook group you want to scrape. Found in the group's URL (e.g., `1439220986320043`). This is the only required parameter to start extraction. | ### What data can you extract? You can download the following data in JSON, CSV, or Excel formats: ```json { ""group_id"": ""987654321"", ""post_id"": ""post_2025121801"", ""content_text"": ""Join us for our annual tech meetup this weekend! RSVP required."", ""author_name"": ""Sarah Chen"", ""post_timestamp"": ""2025-12-18T14:30:22Z"", ""member_count"": 1247, ""engagement_count"": 43, ""attachment_urls"": [""https://cdn.groups.example.com/images/meetup-banner.jpg""] } ```` **Extracted Fields:** - `group_id`: Unique identifier for the Facebook group - `post_id`: Unique identifier for each individual post - `content_text`: Full text content of the post - `author_name`: Name of the user who created the post - `post_timestamp`: ISO 8601 formatted timestamp indicating when the post was published - `member_count`: Total number of members in the group at extraction time - `engagement_count`: Combined count of reactions, comments, and shares - `attachment_urls`: Array of URLs for images, videos, or other media attached to the post *** Whether you need a Facebook group posts scraper for competitive analysis, want to export group posts for sentiment tracking, or require group post extraction for lead generation from group posts, this tool provides reliable access to social media group posts data. Collect group posts data efficiently and build your competitive intelligence pipeline with this cookieless solution." # Actor input Schema ## `groupId` (type: `string`): Group ID ## `maxPages` (type: `integer`): Maximum number of pages to fetch (pagination handled automatically) ## Actor input object example ```json { "groupId": "new york", "maxPages": 1 } ``` # 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("iron-crawler/facebook-group-posts").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("iron-crawler/facebook-group-posts").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 iron-crawler/facebook-group-posts --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=iron-crawler/facebook-group-posts", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Facebook Group Posts Scraper (No Login Required)", "description": "Scrape Facebook group posts at lightning speed. Zero-config API pipeline exports bulk data in JSON/CSV for instant social media intelligence and competitive analysis.", "version": "1.0", "x-build-id": "yRLnF0xYavvTmxhCu" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/iron-crawler~facebook-group-posts/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-iron-crawler-facebook-group-posts", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/iron-crawler~facebook-group-posts/runs": { "post": { "operationId": "runs-sync-iron-crawler-facebook-group-posts", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/iron-crawler~facebook-group-posts/run-sync": { "post": { "operationId": "run-sync-iron-crawler-facebook-group-posts", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "groupId" ], "properties": { "groupId": { "title": "Group ID", "type": "string", "description": "Group ID", "default": "new york" }, "maxPages": { "title": "Maximum Pages", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of pages to fetch (pagination handled automatically)", "default": 1 } } }, "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 } } } } } } } } } } ```