Facebook Group Posts Scraper — group content & engagement

What does Facebook Group Posts do?

Facebook Group Post Scraper turns public facebook.com group pages into structured datasets for monitoring communities, researching public discussions, and tracking buy/sell activity. It extracts post text, permalinks, timestamps, authors, engagement counters, media references, top comments, and Marketplace listing signals without requiring Facebook login cookies.

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Key features

• 🧵 Public group post extraction — collect structured records from Facebook group URLs, including post IDs, canonical permalinks, author names, timestamps, text, media references, comments count, likes, shares, and reaction breakdowns.
• 🔎 Keyword and date filtering — focus runs with a keyword search and onlyPostsNewerThan filters, so recurring jobs can monitor only the posts that matter.
• 💬 Comment-aware output — optionally include top-level comments when Facebook exposes them in the group feed payload, preserving commenter IDs, profile names, text, and comment links.
• 🏷️ Marketplace post detection — detect group posts that point to Marketplace listings and optionally enrich them with listing title, price, status, location, coordinates, and item URL.
• ♻️ Monitoring and incremental runs — use monitoringMode / incrementalMode with a stable stateKey to emit NEW, UPDATED, or unchanged posts according to your workflow.
• 📤 Automation-ready delivery — send results to datasets, compact AI-agent payloads, generic webhooks, Telegram, Discord, Slack, WhatsApp, or MCP connected apps such as Notion, Sheets, Slack, Airtable, and Linear.
• 📊 Clean datasets for analysis — export consistent records for dashboards, alerts, spreadsheets, CRMs, and AI workflows without manual copy-paste from Facebook groups.

What data can you extract from Facebook Group Post?

Each result includes Core listing fields (facebookUrl, inputUrl, facebookId, groupTitle, url, legacyId, id, and text, and more). In standard mode, all fields are always present — unavailable data points are returned as null, never omitted. In compact mode, only core fields are returned.

Enable detail enrichment in the input to fetch each record's detail page — extra fields the search results omit.

Input

The main inputs are a search keyword. Additional filters and options are available in the input schema.

Key parameters:

• startUrls — One or more public Facebook group URLs to scrape posts from, for example https://www.facebook.com/groups/874728723021553
• viewOption — Preferred feed order for the group feed. (default: "CHRONOLOGICAL")
• search — Keep only posts from the provided group URLs whose extracted text contains this phrase.
• onlyPostsNewerThan — Absolute date such as 2026-04-20 or relative duration such as 30 days, 2 weeks, 1 month.
• includeComments — Extract top-level comments when they are present in the group page payload. (default: false)
• enrichMarketplaceListings — Detect Marketplace posts and fetch extra listing fields when a linked item is present. (default: false)
• monitoringMode — Return only posts not delivered in previous runs for the same state key. (default: false)
• incrementalMode — Alias for monitoring mode. Return only posts not delivered in previous runs for the same state key. (default: false)
• maxItems — Maximum number of posts to save. (default: 100)
• compact — Return only core fields. (default: false)
• excludeEmptyFields — Remove null, empty array, and empty object fields from each output item. (default: false)
• stateKey — Optional stable key for monitoring mode.
• ...and 19 more parameters

Input examples

Basic search — Fetch listings from the provided start URL.

→ Full payload per result — all standard fields populated where the source provides them.

{
  "startUrls": [
    {
      "url": "https://www.facebook.com/groups/874728723021553"
    }
  ],
  "maxItems": 50
}

Incremental tracking — Only emit listings that changed since the previous run with this stateKey.

→ First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set emitUnchanged: true to include unchanged records as well.

{
  "startUrls": [
    {
      "url": "https://www.facebook.com/groups/874728723021553"
    }
  ],
  "maxItems": 200,
  "incrementalMode": true,
  "stateKey": "facebook-tracker"
}

Compact output for AI agents — Return only core fields for AI-agent and MCP workflows.

→ Small payload with the most important fields — ideal for piping into LLMs without token overhead.

{
  "startUrls": [
    {
      "url": "https://www.facebook.com/groups/874728723021553"
    }
  ],
  "maxItems": 50,
  "compact": true
}

Output

Each run produces a dataset of structured listing records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console.

Example listing record

{
  "facebookUrl": "https://www.facebook.com/groups/874728723021553",
  "inputUrl": "https://www.facebook.com/groups/874728723021553",
  "facebookId": "874728723021553",
  "groupTitle": "Maths Formulas",
  "url": "https://www.facebook.com/groups/874728723021553/permalink/2480039325823810/",
  "legacyId": "2480039325823810",
  "id": "2480039325823810",
  "text": "Set Theory basics and formulas for quick revision.",
  "time": "2026-07-15T09:15:13.000Z",
  "user": {
    "id": "100000000001",
    "name": "Example Member"
  },
  "feedbackId": "ZmVlZGJhY2s6MjQ4MDAzOTMyNTgyMzgxMA==",
  "topReactionsCount": 39,
  "reactionLikeCount": 31,
  "reactionLoveCount": 5,
  "reactionHahaCount": 1,
  "reactionWowCount": 2,
  "reactionSadCount": 0,
  "reactionAngryCount": 0,
  "commentsCount": 42,
  "sharesCount": 5,
  "likesCount": 31,
  "attachments": [
    {
      "__typename": "Photo",
      "thumbnail": "https://scontent.fbcdn.net/example-photo.jpg",
      "photo_image": {
        "uri": "https://scontent.fbcdn.net/example-photo.jpg"
      }
    }
  ],
  "photoCount": 1,
  "additionalPhotoCount": 0,
  "topComments": [
    {
      "commentId": "2480075832486826",
      "id": "2480075832486826",
      "text": "Nice summary.",
      "threadingDepth": 0,
      "profileId": "100000000002",
      "profileName": "Example Commenter",
      "commentUrl": "https://www.facebook.com/groups/874728723021553/permalink/2480039325823810/?comment_id=2480075832486826"
    }
  ],
  "isMarketplaceListing": false,
  "changeType": "NEW",
  "scrapedAt": "2026-07-15T10:00:00.000Z",
  "source": "facebook.com"
}

Incremental fields

When monitoring mode is on, each record also carries a changeType — NEW or UPDATED by default; set emitUnchanged: true to also receive posts unchanged since the last run. A group's public feed only exposes its newest posts, so a post that has scrolled out of that feed can't be told apart from one that was deleted — this actor tracks new and changed posts but never claims one is gone for good.

How to scrape Facebook Group Post

1. Go to Facebook Group Posts in Apify Console.
2. Enter a search keyword.
3. Set maxItems to control how many results you need.
4. Enable includeDetails if you need the extra detail-page fields.
5. Click Start and wait for the run to finish.
6. Export the dataset as JSON, CSV, or Excel.

Use cases

• Extract listing data from Facebook Group Post for market research and competitive analysis.
• Monitor new and changed listings on scheduled runs without processing the full dataset every time.
• Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode.
• Export clean, structured data to dashboards, spreadsheets, or data warehouses.

How much does it cost to scrape Facebook Group Post?

Facebook Group Posts uses pay-per-event pricing. You pay a small fee when the run starts and then for each result that is actually produced.

• Run start: $0.0072 per run
• Per result: $0.00225 per listing record

Example costs:

• 10 results: $0.03
• 25 results: $0.063
• 100 results: $0.23
• 200 results: $0.46
• 500 results: $1.13

Example: recurring monitoring savings

These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions.

Example setup: 250 listings per run, daily polling (30 runs/month). Costs scale linearly with the number of listings.

Churn rate	Full re-scrape run cost	Incremental run cost	Savings vs full re-scrape	Monthly cost after baseline
5% — stable niche query	$0.57	$0.04	$0.53 (94%)	$1.06
15% — moderate broad query	$0.57	$0.09	$0.48 (84%)	$2.75
30% — high-volume aggregator	$0.57	$0.18	$0.39 (69%)	$5.28

Full re-scrape monthly cost at the same cadence: $17.09. First month with incremental costs $1.59 / $3.23 / $5.67 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply.

Platform usage (compute and proxies) is billed separately by Apify based on actual consumption. Incremental runs consume less on result processing, though fixed per-run overhead stays the same.

FAQ

How many results can I get from Facebook Group Post?

The number of results depends on the search query and available listings on Facebook Group Post. Use the maxItems parameter to control how many results are returned per run.

Does Facebook Group Posts support recurring monitoring?

Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset.

Can I integrate Facebook Group Posts with other apps?

Yes. Facebook Group Posts works with Apify's integrations to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes.

Can I use Facebook Group Posts with the Apify API?

Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages.

Can I use Facebook Group Posts through an MCP Server?

Yes. Apify provides an MCP Server that lets AI assistants and agents call this actor directly. Use compact mode, a single descriptionFormat, and excludeEmptyFields to keep payloads manageable for LLM context windows.

Is it legal to scrape Facebook Group Post?

This actor extracts publicly available data from Facebook Group Post. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant.

Your feedback

If you have questions, need a feature, or found a bug, please open an issue on the actor's page in Apify Console. Your feedback helps us improve.

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Getting started with Apify

New to Apify? Create a free account with $5 credit — no credit card required.

1. Sign up — $5 platform credit included
2. Open this actor and configure your input
3. Click Start — export results as JSON, CSV, or Excel

Need more later? See Apify pricing.

Disclaimer

This actor accesses only publicly available data on facebook.com. You are responsible for how you use the extracted data — in particular any personal information such as names, phone numbers, or email addresses — and for complying with Facebook Group Posts's terms of use, applicable data-protection law (including the GDPR where it applies), and the anti-spam rules of your jurisdiction.

This actor is not affiliated with, endorsed by, or connected to Facebook Group Posts.

Search keywords

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