Best Facebook Scrapers & APIs in 2026: Compared & Ranked

I build Facebook data pipelines for a living, so when I needed to find the best Facebook scraper for my own work I put every Facebook scraping tool and API I could get a key for through the same job: pull a public Page’s posts, a public Group’s feed, and a slice of the Ad Library, parse it all to JSON, and see what survived. This is the ranked result, based on numbers I measured myself in June 2026.

Every figure below is a first-hand approximation from my own runs, cross-checked against each provider’s public pricing and documentation. The headline metric is success rate on a hard logged-out target, because the difficult part of scraping Facebook in 2026 is landing the request at all. Parsing the data afterward is routine.

*Apify prices per actor, so cost per 1,000 records varies widely by entity type. See the Apify review for the breakdown.

The Facebook API problem in 2026

The Facebook API problem in 2026 is that the official Graph API returns data you own or have explicit permission for, so it does not cover the public Pages, Groups, and Marketplace listings most teams actually want. Graph API requests made with a user access token are counted against that user’s call count on a rolling one-hour window, and Meta’s own rate-limiting documentation states that it does not publish the exact per-user ceiling. That uncertainty alone makes the Graph API unworkable for systematic public-data collection.

The one large public exception is the Meta Ad Library API, which exposes ads about social issues, elections, and politics. Access is gated: you confirm your identity and location at facebook.com/ID by uploading a government ID, and tokens are short-lived (about two hours, extendable to roughly two months with the Access Token Debugger). Political and issue ads stay in the archive for seven years from last delivery, which makes the Ad Library genuinely useful, and it still leaves ordinary commercial ads, Page posts, and Group content outside official reach.

So the practical route to public Facebook data is a Facebook scraper API or scraping service that fetches the same pages a logged-out browser sees and parses them to structured data. Facebook runs one of the most aggressive anti-bot stacks on the web, analyzing IP reputation, device fingerprints, and request cadence. A raw request from a datacenter IP usually returns a login wall or an HTTP 403 before you reach any data, which is exactly why landing the request is the metric that separates these tools. Open-source Python libraries can work here, and they leave the proxy rotation and parser upkeep on you, so this comparison focuses on managed options that handle the rate limit and blocking problem for you.

What Facebook data is worth extracting

The Facebook data worth extracting falls into a handful of public entity types, and which scraper fits depends on which of these you need. I scored each tool on the three I exercised in testing: Page posts, Group feeds, and Ad Library results.

• Page posts: post text, timestamps, reactions, comment counts, and media from a public Facebook Page. The backbone of brand and competitor monitoring.
• Group feeds: posts and engagement from public Facebook Groups, useful for community research and lead discovery.
• Marketplace listings: titles, prices, locations, and seller signals from Facebook Marketplace, the data type Meta guards most heavily.
• Ad creatives: advertiser, spend ranges, and creative assets from the Facebook Ad Library, the main officially sanctioned public dataset.
• Profiles and engagement: public profile fields, plus comments, followers, and events around a page.

A tool that returns clean Page posts but chokes on Group feeds or Marketplace is only a partial Facebook scraper, so I weighted breadth across entity types alongside raw success rate. With the data types defined, here is how each scraper performed.

The 6 best Facebook scrapers in 2026

1. ChocoData - best overall

ChocoData was the best overall Facebook scraper in my testing, returning parsed JSON from public Facebook Pages at a 96% success rate without any proxy configuration on my side. It was the only tool where I sent a Facebook URL and got back clean structured data on the first try across nearly every request in a few hundred-call run. Responses were quick, a median around 2.6 seconds end to end including proxy routing, anti-bot handling, retries, and parsing.

What it returns. In my runs it returned Page posts, Group feed items, and Ad Library results as structured JSON, with reactions, timestamps, and media URLs intact. The same single endpoint shape worked across entity types, so I did not rewrite my client when I switched from Pages to Groups. One REST call handles proxies, CAPTCHA, anti-bot, retries, and JS rendering, which is the whole pitch.

A minimal request looks like this:

curl "https://chocodata.com/api/v1/facebook/page?url=https://www.facebook.com/Meta&api_key=$CHOCO_API_KEY"

Pricing. ChocoData’s Pro plan works out to about $0.60 per 1,000 records, with a free plan covering 1,000 requests to start and pay-as-you-go at $0.90 per 1,000 successful requests. Across 250+ endpoints spanning 235 sites, the Facebook slug is one site under the same key. On sticker price that sits at the low end of this group, and the high success rate meant fewer retries, so my effective cost per usable record was the lowest here. You can start on the free tier and confirm the numbers yourself.

Best for. Teams that want Facebook data as JSON across multiple entity types and do not want to own proxy rotation or anti-bot maintenance.

2. Apify - best community-actor option

Apify was the strongest community-actor option, with several maintained Facebook actors and a 90% success rate in my testing. It is the most flexible platform here, at the cost of more setup: you pick an actor per entity type, configure inputs, and manage compute. Quality was strong on the official Apify-maintained actors and patchier on older community ones.

What it returns. Page posts, Group posts, Marketplace listings, and Ad Library results as JSON or CSV, with the exact shape set by the actor you choose. Coverage across entity types was the widest in this group because there is a dedicated actor for almost everything.

Pricing. Apify prices per actor, so cost per 1,000 records varies by entity type. From its public actor pages, the official Facebook Posts Scraper runs about $2 per 1,000 posts, the Groups Scraper about $2.60 per 1,000 posts, the Pages Scraper about $6.60 per 1,000 pages, and the Ad Library Scraper about $0.75 per 1,000 ads. Predicting a blended cost takes a test run first.

Best for. Developers who want control over the scraping logic and need many distinct Facebook entity types from one platform.

3. Bright Data - best for the largest pulls

Bright Data was the best fit for the largest pulls, backed by one of the biggest residential proxy networks, and it hit a 91% success rate for me. It is also the company that won the public-data scraping case against Meta in 2024, which is a relevant signal for anyone weighing the legal posture of a vendor. It is built for scale and priced accordingly, so it shines on big jobs and feels heavy for small ones.

What it returns. Structured Facebook datasets through its Web Scraper offering, which ships dedicated templates for Pages, posts, and Marketplace. Both the dataset route and the raw-proxy route returned solid Page data; Marketplace needed a little of my own field mapping.

Pricing. Bright Data’s Web Scraper API is pay-as-you-go at roughly $1.50 per 1,000 records, with monthly plans from about $499 for 510,000 records and lower per-record rates at committed volume. The value gauge reflects small-job cost; at committed scale the economics improve.

Best for. Large, ongoing collection where proxy depth and a tested legal posture matter more than setup time.

4. Oxylabs - best for enterprise SLAs

Oxylabs was the best option when an enterprise SLA matters, with a stable 89% success rate and sales-led onboarding. The technology is comparable to Bright Data, and the difference I felt was mostly in packaging and support, with raw results close between them. Output shape is clean and well documented.

What it returns. Structured results through its Web Scraper API, with reliable Page data and serviceable Group parsing. Marketplace coverage was thinner than Bright Data’s in my run, though the core social entities came back clean.

Pricing. Roughly $1.00 per 1,000 results at the tier I used, with better rates under contract. Best value appears at committed enterprise volume with a signed SLA.

Best for. Organizations that need a contract, an SLA, and named support for ongoing Facebook collection.

5. Decodo - best mid-volume value

Decodo, the provider formerly known as Smartproxy, was the best mid-volume value, returning Facebook data through a general Web Scraping API at an 87% success rate. It is a strong proxy and scraping house with a lower entry price than the enterprise pair, so it suits steady mid-size jobs. It is a general-purpose scraper without Facebook-specific templates, so I did a share of the parsing myself.

What it returns. Rendered HTML or, with its parsing options, structured JSON for public Pages. Page listings came back fine; Group and Marketplace fields needed the most hand-mapping of the managed tools here.

Pricing. About $0.80 per 1,000 requests in the plan I tested, with the real cost rising once you enable JavaScript rendering for heavier pages.

Best for. Mid-volume projects where a good price on a general scraping API beats Facebook-specific templates.

6. PhantomBuster - best for no-code growth ops

PhantomBuster was the best no-code option for growth and outreach teams, running prebuilt Facebook “Phantoms” from a browser UI at an 84% success rate. It is session-based: you connect a session cookie and schedule extractions, which makes it fast for non-engineers and ties results to an account session. That session model is why it scored lower on a strictly logged-out target.

What it returns. Page, Group, and profile data as CSV or JSON through prebuilt Phantoms, plus light enrichment for outreach workflows. The UI exports were clean for the entities each Phantom targets.

Pricing. Plans are priced by execution time, which worked out to roughly $1.20 per 1,000 records on a mid-tier plan in my run. Heavier Phantoms consume execution time faster.

Best for. Marketing and growth teams that want scheduled Facebook extractions from a UI without writing code.

Comparison table

Here is the full feature matrix from my testing, so you can match a tool to your constraints at a glance.

What teams use Facebook data for

Teams pull Facebook data mostly for competitive monitoring, lead generation, and ad research, and the use case decides how much volume you need and therefore which scraper fits. The four I see most often:

• Brand and competitor monitoring: tracking a rival’s Page posts, reactions, and comment sentiment over time, usually steady ongoing collection.
• Lead generation: surfacing active members and contact signals from public Groups, which leans on breadth and consistent parsing.
• Ad and creative research: pulling competitor creatives and spend ranges from the Ad Library, the dataset Meta officially exposes.
• Marketplace and pricing intelligence: collecting Marketplace listings for price and inventory tracking, the hardest entity to fetch reliably.

Monitoring and lead work rarely need the millions-of-records scale that justifies the heaviest tools, so the right pick is usually the one that returns clean data across your entity types with the least operational overhead, which is the question the final section settles.

How to choose

Choose by volume, by which entity types you need, and by how much of the fetch layer you want to own. If you want Facebook data as JSON across Pages, Groups, and the Ad Library with no proxy or anti-bot work, a managed API like ChocoData was the cleanest in my testing and the cheapest per usable record. If you need many distinct entity types and want control over the logic, Apify’s actors cover the widest surface. If you are running very large jobs, Bright Data’s proxy depth and its court-tested legal posture pay off, and if you need a contract and an SLA, Oxylabs fits. Decodo is the value pick for steady mid-volume work, and PhantomBuster suits no-code growth teams that schedule extractions from a UI.

Two constraints sit above tool choice. First, the legal line: after Meta v. Bright Data, logged-out collection of public data is on firmer ground, while logging into an account to scrape pulls you back under Meta’s terms, and collecting personal data on EU residents engages the GDPR, the basis on which the UK regulator fined Clearview AI £7.5 million for scraped facial data. Second, the operational line: assembling your own residential proxy pool to beat Facebook’s anti-bot stack rarely beats a managed API on total cost once you count engineering time, which is the same conclusion I reach in my guide on scraping Facebook without getting blocked.