Facebook Reviews Scraper

Collect public Facebook Page recommendations into structured review rows with text, recommendation state, reviewer details and dates when available. Facebook Reviews Scraper accepts Page URLs or numeric IDs without a Facebook login. Public availability can be smaller than the Page's displayed review total.

Quick start

Paste a public Page URL, choose a small limit and start the Actor. Open the dataset to export JSON, CSV or Excel, and check RUN_SUMMARY for Pages that returned no rows.

{
  "startUrls": [{ "url": "https://www.facebook.com/copperkettleyqr/reviews" }],
  "maxItems": 5,
  "maxReviewsPerPage": 5
}

Supply at least one startUrls entry or numeric pageIds entry. The existing residential connection default applies when no proxy setting is supplied.

Prefer a video guide? This short Apify walkthrough shows you how to set up and run an Actor. It uses a different Actor, but the setup steps are the same.

Ready-to-run examples

Choose a public example to see its settings before starting a run:

• Export Facebook Reviews by Page ID
• Download Facebook Reviews with Photos
• Export Facebook Page Reviews and Recommendations

What you get

• Accepts Page URLs, /reviews URLs, and numeric Page IDs.
• Handles multiple Pages in one run and removes duplicate review stories.
• Follows Facebook's available logged-out continuation pages until the requested limit, the public feed ends, or a bounded safety limit is reached.
• Returns both recommended and not-recommended stories.
• Preserves exact public timestamps, stable story and post IDs, reviewer fields, Page score/count, engagement counts, tags, and optional attached-photo URLs when Facebook exposes them.
• Writes a per-input RUN_SUMMARY record so unavailable, blocked, invalid, empty, and duplicate-only inputs are not hidden.

Who is it for?

• Reputation teams reviewing public Page recommendations and feedback text.
• Hospitality and local-business researchers comparing selected known Pages.
• Customer-research teams analyzing returned recommendation tags and comments downstream.
• Data teams maintaining source-linked review exports in their own systems.

How you can use the data

• Review a small known-Page sample. Use the existing restaurant reviews URL with small global and per-Page caps. Keep id, reviewId, text, isRecommended, source links and collection time together. Recommendation state is not a star rating.
• Compare selected business Pages. Inspect available review text, recommendation tags and Page score/count fields in your own report. The displayed Page total is context rather than a promise that every review can be exported.
• Inspect public review attachments. Enable the supported photo option when useful and inspect returned best-resolution photo URLs. Empty reviewer or photo fields mean unavailable public data rather than a reason to infer missing content.
• Build your own review observations. Save a small input as a task, schedule it daily or weekly and connect your own finished-run integration. Compare reviewId or id against saved exports to identify new feedback downstream, and check RUN_SUMMARY for unavailable or blocked Pages.

Input settings

Setting	JSON key	Description
Facebook Page URLs	startUrls	Public Page, /reviews, or numeric Page URLs. Post, group, reel, and video URLs are rejected.
Facebook Page IDs	pageIds	Optional numeric Page IDs. Can be combined with URLs.
Maximum reviews	maxItems	Global dataset-row limit, from 1 to 1,000.
Maximum per Page	maxReviewsPerPage	Per-Page limit from 1 to 250. The form defaults to 10. When omitted in API input, it follows maxItems, capped at 250.
Include photos	includeReviewPhotos	Include one best-resolution public URL per attached review photo.
Proxy	proxyConfiguration	Residential by default. The input help explains managed proxies, custom proxies and explicit no-proxy settings.

Example inputs

Use the Quick start input as a small first run. Adjust the fields described above for your own data.

Output data

Each dataset item is one public recommendation story.

Field	Description
inputUrl, inputType	Original input and whether it was a URL or Page ID.
facebookUrl	Normalized Page reviews URL.
pageName, pageUsername	Public display name and vanity name.
pageId, facebookId	Numeric Facebook Page ID.
pageRecommendationPercent, pageReviewCount	Public Page-level recommendation score and displayed review count.
id, reviewId, legacyId	Facebook story ID, permalink ID, and legacy post ID.
url	Direct public review-story URL when exposed.
user	Compatibility object with reviewer ID, name, profile URL, and profile picture.
reviewerId, reviewerName	Flat reviewer fields for CSV and spreadsheet workflows.
reviewerProfileUrl, reviewerProfilePic	Public reviewer links when exposed.
isRecommended	true for recommends and false for doesn't recommend.
date, dateText	Exact ISO timestamp and visible date label.
text, tags	Review text and public recommendation tags.
likesCount, commentsCount	Public engagement totals.
reviewPhotos, photos	One best-resolution public URL per attached review photo when requested and exposed.
status, stopReason, source, scrapedAt	Extraction provenance and run-time context.

Example output

Selected fields from an existing public review, with reviewer identity and story identifiers omitted:

{
  "facebookUrl": "https://www.facebook.com/copperkettleyqr/reviews",
  "pageName": "The Copper Kettle Restaurant",
  "pageUsername": "copperkettleyqr",
  "pageId": "100064027242849",
  "pageRecommendationPercent": 94,
  "pageReviewCount": 201,
  "isRecommended": true,
  "date": "2024-09-11T17:57:58.000Z",
  "text": "They offers a cozy atmosphere, friendly service, and a menu of tasty comfort food at reasonable prices. It’s a great spot for casual dining.",
  "tags": ["Child-friendly", "Fast delivery", "Cosy atmosphere"],
  "likesCount": 0,
  "commentsCount": 0,
  "photos": [],
  "source": "facebook-public-preloaded-review-feed"
}

Download your results

Open your run's dataset, choose Export and select JSON, CSV or Excel. JSON keeps nested fields together. CSV and Excel are useful when you want to review the records in a spreadsheet.

See Apify's download and export guide for the available formats and field options.

Pricing

The start event is charged after target validation and before Facebook work. A run that later saves no reviews or fails can still incur this charge, and a restarted execution can incur another start event.

The primary item event applies to each saved review row. Per-input statuses, summaries, checkpoints and diagnostics are not review rows.

See the live Pricing tab for current rates and plan discounts.

Tips for best results

• Begin with one Page and a small review cap. Inspect the public feed and available fields before expanding your sample.
• Keep the existing connection behavior in mind. Residential is the default, while explicit direct egress can vary by location.
• Use numeric Page IDs when you already have them. Supported Page and reviews URLs are normalized automatically.
• Read dataset and summary outcomes together. A zero-row Page is not automatically a failure, but a no-review run fails if every reported input is blocked, invalid or errored.
• Keep story identifiers for your own comparison. Use saved exports to identify new feedback rather than assuming a schedule supplies automatic deduplication.

Limits and caveats

• Facebook does not expose every review counted on a Page to logged-out visitors. The Actor returns the public stories present in Facebook's response and does not promise the full displayed total.
• The Actor follows Facebook's public continuation cursor when available, but the public feed can still end before the displayed Page review count.
• Facebook orders public recommendations by its own relevance logic, not necessarily chronologically.
• Reviewer fields and photos can be null or empty when Facebook does not expose them publicly.
• The Actor does not accept account credentials, cookies, private sessions, access tokens, groups, profiles, messages, or other non-public surfaces.
• Process public reviewer data only for a legitimate purpose and with appropriate retention and access controls.

Automation and integrations

Save your settings for next time

Once you have an input that works for you, save it as an Apify task. This keeps your settings together so you can use them again without filling in the form from scratch.

Run on a schedule

Need fresh results regularly? You can schedule the Actor or a saved task to run at a time that suits you.

Each scheduled run collects the data again. If you want to compare results or highlight changes, add that step in your own workflow.

Send results to your other tools

Use n8n, Make or Zapier to connect this scraper to the rest of your workflow. For example, you could pass its results to an AI assistant or add records to a spreadsheet. Follow the Apify integration guides for your chosen tool.

For a custom connection, an Apify webhook can notify your app when a run finishes or fails. Your app can then fetch the results or handle the failure.

API usage

Want to collect this data from your own app or automation? The examples below send input to the scraper and show how to collect its results.

The Node.js and Python examples wait for the run to finish before reading its results. The cURL example starts the run and returns its details. Wait for that run to finish, then use its defaultDatasetId to fetch the results.

For setup instructions, see Apify's JavaScript client guide, Python client guide and Actor runs API reference.

cURL

curl -X POST 'https://api.apify.com/v2/acts/fetch_cat~facebook-reviews-scraper/runs' \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H 'Content-Type: application/json' \
  --data @- <<'JSON'
{
  "startUrls": [
    {
      "url": "https://www.facebook.com/copperkettleyqr/reviews"
    }
  ],
  "maxItems": 5,
  "maxReviewsPerPage": 5
}
JSON

Node.js

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: process.env.APIFY_TOKEN });
const run = await client.actor('fetch_cat/facebook-reviews-scraper').call({
  "startUrls": [
    {
      "url": "https://www.facebook.com/copperkettleyqr/reviews"
    }
  ],
  "maxItems": 5,
  "maxReviewsPerPage": 5
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python

import os
from apify_client import ApifyClient

client = ApifyClient(os.environ['APIFY_TOKEN'])
run = client.actor('fetch_cat/facebook-reviews-scraper').call(run_input={'startUrls': [{'url': 'https://www.facebook.com/copperkettleyqr/reviews'}], 'maxItems': 5, 'maxReviewsPerPage': 5})
print(client.dataset(run['defaultDatasetId']).list_items().items)

MCP and AI agents

You can ask your AI assistant to collect data with Facebook Reviews Scraper and help you work with the results. The scraper returns the data, and your assistant can then summarize it, compare records or prepare notes.

Connect your assistant through the Apify MCP server. MCP gives your assistant a way to find this scraper, run it and read the results. Follow the official setup and sign-in guide for your app.

Easier setup with an Apify plugin

If you use a supported coding assistant, the official Apify plugin can set up the connection for you. It connects your assistant to Apify and includes instructions for common tasks. Follow the guide for your particular app.

Use Apify AI in Console

Prefer to keep everything in Apify? Open Apify AI in Console and ask it to find Fetch Cat's Facebook Reviews Scraper. You can describe the data you want and ask questions about the results.

Apify AI is currently in beta. It asks for confirmation before starting an Actor, and normal run charges apply.

Choose your assistant

• Claude and Claude Code (Anthropic): Apify setup guide.
• ChatGPT and Codex (OpenAI): Apify setup guides.
• Grok Bot (xAI): Apify plugin guide.
• Gemini CLI (Google): MCP server setup guide. Use the server URL below with the HTTP configuration supported by Gemini CLI.

Connect just this scraper

To keep your setup focused on this scraper, add this server configuration to a compatible MCP client:

{
  "mcpServers": {
    "apify": {
      "url": "https://mcp.apify.com?tools=fetch_cat/facebook-reviews-scraper"
    }
  }
}

Sign in to Apify when your client asks. If your client uses a Bearer token instead, follow its setup guide and keep the token in its secure configuration. Configuration formats vary by app, so use the linked guide if your client needs a different format.

Use Apify's general server

Already connected to the general Apify MCP server at https://mcp.apify.com? You can use it to find this scraper without adding another server. Ask your assistant to use Facebook Reviews Scraper by Fetch Cat, or give it the identifier fetch_cat/facebook-reviews-scraper.

Your assistant can check the available settings and retrieve the results from the returned run. If the run is still working, it should follow that run rather than start it again. Both connection options use Apify's hosted service.

Example requests

• “Use Fetch Cat’s Facebook Reviews Scraper to collect up to 5 public recommendations from https://www.facebook.com/copperkettleyqr/reviews, with at most 5 from the Page. Show review text, recommendation state and source links without treating it as a star rating.”
• “Collect at most 3 public recommendation stories per Page from the 2 numeric Page IDs I provide, with a total cap of 6. Keep review IDs and dates so I can compare them with my own saved exports.”
• “Retrieve up to 3 recommendations from my supplied Page reviews URL with photos enabled. Show available photo links and reviewer fields, and explain blocked, empty or partial outcomes without claiming the full displayed review total.”

Normal Apify charges apply. Check the live Pricing tab before asking your assistant to run a larger batch.

Pay with x402

If your AI agent has a funded wallet, it can pay for Apify usage through x402. This experimental option lets an agent use Apify without a conventional account.

Apify AGI provides a prepaid API token with a spending cap after payment. Your agent can use that token to run this scraper through the Apify API or an authenticated MCP connection.

Some MCP setups also support paying for each request directly. That is a different payment option, so check the official guide for its availability.

Follow the official guide for wallet setup, supported payment options and current terms. Apify handles the payments. Keep wallet keys and payment tokens in your agent's secure configuration.

Other ways for agents to pay

Apify also supports MPP for prepaid access through AGI and Skyfire for eligible Actors. If your agent already uses one of these, see the agentic payment guide to choose the right setup.

Run summary

The default key-value store contains RUN_SUMMARY. It reports outcomes for processed, normalized Pages and invalid inputs. Repeated URLs are combined. Pages not reached before a limit may have no status:

• ok — public reviews were extracted, or the second form of a duplicate Page produced no additional rows.
• no_public_reviews — the Page loaded but exposed no semantic public recommendation.
• unavailable — the Page/reviews surface is unavailable or disabled to logged-out visitors.
• blocked — Facebook returned a security/interstitial block.
• invalid — the input is not a supported Facebook Page input.
• error — navigation or parsing failed for that input.

RUN_CHECKPOINT records completed and pending Pages and the Actor checks existing dataset rows when resuming. A restarted execution can incur another start event. Summary, checkpoint and diagnostic records are best-effort and may be absent after a storage failure.

FAQ

Does this require a Facebook login, cookies, or access token?

No. It reads only the Page data Facebook makes available to logged-out visitors.

Why is the dataset smaller than the Page's displayed review count?

Facebook can expose only a subset of the displayed total to logged-out visitors. The Actor reports the Page count for context but does not invent or bypass unavailable reviews.

Can I export to CSV, Excel, or JSON?

Yes. Apify datasets support CSV, Excel, JSON, JSONL, XML, RSS, and API access.

Why is a reviewer field or photo empty?

The public response does not always include every reviewer link, profile image, permalink, or attachment. Missing values remain empty instead of being guessed.

What should I check when a Page returns no rows?

Open RUN_SUMMARY first. It distinguishes no public recommendations, an unavailable reviews surface, a Facebook block, invalid input, and a processing error.

Related Actors

• Facebook Comments Scraper — Collect visible public post comments with text, displayed dates and available author and engagement fields.
• Google Maps Reviews Scraper — Collect visible place reviews with text, ratings and available reviewer details for location-feedback analysis.
• Trustpilot Reviews Scraper — Collect public company reviews, ratings and visible business replies for reputation research.
• Booking Reviews Scraper — Collect guest-review text, ratings and available stay details from the loaded public Booking.com review page.
• Shopify App Reviews Scraper — Collect public Shopify App Store reviews, star ratings and visible developer replies for app research.

Support and feedback

For custom additions or integrations, email hello@fetchcat.dev.

Found an error or have a feature request? Open an issue with the run URL, a non-sensitive input example and what you expected.

Need help sharing it? See Apify’s guide to sharing a run when reporting an issue. Sharing a run can give the developer access to its input, logs and results, so use a run that contains no sensitive data. Please leave out API tokens, passwords, cookies, private documents and personal data. Use a public sample URL or a redacted example instead.

Tried this scraper? We'd love to hear how it worked for you. Leave a review to help others choose the right tool and help us improve it. Your feedback means a lot to us.

Made with care for curious people, AI agents and the possibilities in data. ♥