What Is the Best API for Social Media Scraping in 2026?

Ask which API is best for social media scraping and the answer comes back as a list of general-purpose scrapers. That list is not wrong, but it answers a question about vendors when the thing in your way is the platforms.

Six networks, six different page structures, six different sets of what is public, and no single scraper that is best at all of them. Monid is the OpenRouter for agent tools, so we resell most of the options below rather than being one of them, which is why this can be a comparison rather than a pitch.

Fair disclosure: you are on the Monid blog. The section near the end says where a single vendor beats us, and it is not a token paragraph.

Why is one API never enough for social?

Because the platforms diverge in the two places that decide everything: what they expose publicly, and what shape it comes back in.

TikTok hands over a profile and its full post history cheaply, because that is what the page renders. LinkedIn withholds most identity from a logged-out visitor, so an employee list comes back with names missing. Instagram returns rich engagement on public accounts and nothing at all on private ones. X, YouTube and Reddit each have their own version of the same story.

A generic scraper handles the fetching, which is the part that is close to solved. What it does not do is know that a TikTok profile record and a LinkedIn profile record are different objects with different missing fields. That knowledge lives in per-platform endpoints, and it is why the catalogue for social is a list of specialists rather than one tool.

The corollary is the practical one: a serious social project uses several endpoints, so the thing to optimise is not which vendor, it is how much friction each new one adds. That is a different question, and it has a different answer.

📖 See also Apify vs TikHub for TikTok scraping, which takes one network and compares two providers on it directly.

What is the best API for social media scraping?

The one that covers the network you are on, and there are three shapes worth knowing.

Per-platform specialists. TikHub for TikTok, X, YouTube and Instagram; harvestapi for LinkedIn. Deep coverage of one network, records that match how that platform actually works.

Generalist actor marketplaces. Apify's actors cover many platforms with a shared interface. Broader, and the depth varies by actor.

Aggregation layers. One key over several providers, so the friction of adding the fourth platform is a parameter rather than a signup. Monid is this shape.

For agents

Grab an API key at app.monid.ai, then paste this to your agent and hand it the key:

set up https://monid.ai/SKILL.md

It learns the whole discover, inspect, run workflow itself. More in the agent quickstart.

For humans

npm install -g @monid-ai/cli
monid keys add -k <your-key> -l main

Start by asking what covers your network

monid discover -q "tiktok profile posts"
monid discover -q "twitter user tweets"
monid inspect -p apify -e /apidojo/tiktok-profile-scraper

Both discover and inspect are free, so surveying the field for a new platform costs nothing. That is the step most comparisons skip, and it is the one that stops you buying before you know whether the fields you need are in the payload.

How do I build a lead enrichment workflow that finds social profiles?

Work from the identifier you hold, and do not try to do it in one call.

This question comes up constantly in automation communities, and it goes wrong the same way each time: someone looks for a single endpoint that turns a name into every profile that person has. That endpoint does not exist, because the platforms do not share identity.

What works is a chain, cheapest step first.

Start from the strongest identifier. A company domain or a LinkedIn URL is worth far more than a name. pdl /v5/company/enrich turns a domain into a company record; harvestapi/linkedin-company-employees turns a company URL into people.

Filter before you enrich. Enrichment costs an order of magnitude more than a lookup, so cut the list first on whatever you already have. Paying premium rates to learn about people you will never contact is the most common waste in this pipeline.

Add social last, and only where it earns its place. A TikTok or Instagram handle matters for creator work and rarely for B2B. Pull it when the use case actually reads it.

The reason to run this on one balance is that the chain crosses three or four providers. Wire it vendor by vendor and you have four signups, four keys and four invoices before you know whether the workflow is any good.

📖 See also turning a LinkedIn profile URL into an enriched lead for the step-by-step version.

Which endpoint should I use for which network?

Verified present on 2026-08-14 with monid discover. The billing column states the shape rather than a figure, because figures move and monid inspect prints the current one for free.

What one profile record actually contains

We pulled an Instagram profile on 2026-08-14 to count rather than describe. 69 fields, 16 of them empty.

The useful ones are not the follower count. is_verified and is_private decide whether the rest of the record means anything. biography and external_url are where a creator states what they do and where they sell, which is the text you feed a model. business_email and public_email exist as fields and were null here, which is the honest answer to "can I get contact details from a profile": sometimes, on business accounts that chose to publish them, and you cannot plan around it.

Sixteen empty fields on a major account is the number to sit with. These records are sparse by default, and the sparsity is not random: it tracks what that specific account chose to publish. A pipeline that assumes a field is present because it appeared in the schema will break on the second account it sees, not the hundredth.

The other thing that happened

Our first call, against a different well-known account, returned "This account does not exist." The account plainly does exist. The second call, using the endpoint's own documented example username, returned a full record.

We are reporting this as one observation rather than a verdict, because one false negative is not a pattern and we did not chase it further. What it does illustrate is the part worth designing for: the call was charged. A wrong answer bills the same as a right one, so a bulk job that treats "does not exist" as ground truth will quietly drop real accounts and pay for the privilege.

Handle it the way you would any noisy source. Treat a not-found as a retry candidate rather than a fact, and if an account matters, confirm it a second way before writing the absence into your data.

What does social data actually cost?

Less than people expect per record, and the shape matters more than the unit.

Per call means one request, one price, however much comes back. TikHub's social endpoints work this way, which suits lookups: fetching one user's posts costs the same whether they have ten or a hundred.

Per result means the bill tracks records. Apify's actors mostly work this way, which suits sweeps: you pay for what you collect, and a limit parameter is also a spending cap.

Using either in the wrong shape is where surprise bills come from. A per-result endpoint pointed at a thousand profiles with no cap is not the same purchase as a per-call lookup, even when the unit price looks similar.

One caution we learned by measuring rather than reading, this month, on our own catalogue: the stated shape does not always predict the charge. Two endpoints described one way billed another, and we published the numbers, including the one that made us look worst. Before a sweep, run one small call and read the actual charge. Live per-endpoint pricing is at monid.ai/tools.

The field that decides whether the rest is worth anything

Every platform here exposes some version of a public-versus-private flag, and it is the field to branch on before you read anything else.

The reason is that a private account does not return an error. It returns a record, and the record is thin: identity and a follower count, with everything you actually wanted absent. A pipeline that checks for an error and finds none will happily store that thin record as though the account had no posts, no bio and no engagement. The account has all three; you just cannot see them.

So the shape that works is a branch, not a filter. Read the privacy flag first, and route. Public accounts go down the normal path. Private ones get marked as unreadable rather than as empty, which is a different fact and the one you want in the database.

The same logic applies to verification. is_verified costs nothing extra and it is the cheapest signal you have for whether an account is who it claims, which matters most in exactly the workflow where people skip it: matching a person to a handle during enrichment.

Rate is a platform property, not a vendor one

One more thing worth knowing before you plan a sweep.

How fast you can pull is set by the platform far more than by which vendor you buy from. Two providers reading the same network hit the same underlying limits, so a vendor promising dramatically more throughput on a public source is either using more infrastructure, which costs more, or reading something less complete.

The practical version: plan sweeps by how long they take, not by how much they cost. A hundred thousand profiles is not a lunchtime job on any vendor, and discovering that after committing to a delivery date is worse than discovering it in the schema. Run a small batch, time it, and multiply before you promise anything.

When should you not use Monid?

You only work on one network, at volume, forever. If your product is a TikTok analytics tool, buy TikHub directly. One vendor, direct support, better unit economics at scale, and the aggregation argument buys you nothing when there is nothing to aggregate.

You need the platform's own analytics. Public scraping returns what a logged-out visitor sees, which is not a creator's private insights. For accounts you own, the platform's official API after app review is the right tool, and no scraper substitutes for it.

You need contractual guarantees. A marketplace optimises for breadth and switching cost, not for an SLA with your name on it.

And the caution about us. Our price metadata has disagreed with real charges on endpoints we resell. We found it by measuring, corrected it publicly, and the working rule until it is fixed is to verify with a small run rather than trust the listing. That applies to every vendor in this category, including the ones we sell.

Conclusion

There is no best social media scraping API, because social is not one problem. TikTok gives up a full post history cheaply; LinkedIn anonymises most of what you want; Instagram returns nothing at all for a private account. Those are properties of the platforms, and no vendor choice changes them.

What you can choose is how much a new network costs you in friction. On a per-vendor setup the fourth platform is a signup, a key and an invoice. On a catalogue it is a parameter.

Two things matter more than the pick. Whether the endpoint bills per call or per record, because that decides your architecture and not just your bill. And whether you check with a small run before a big one, because a listing describes a vendor's intent and only a charge describes the charge.

Start with the free part: monid discover -q "<your network>" lists what exists and monid inspect shows the schema and price without spending anything. Begin at monid.ai.

FAQ

Last updated August 2026.