A Twitter scraper for public profiles and tweets
Public profiles and tweets without the $42K API.
The Kavex Twitter scraper exports public profile data and tweets from X without an enterprise API contract. Paste profile URLs, @handles or tweet links and get back bios, follower counts, locations and the latest tweets with their engagement numbers. It is built for outbound research and brand monitoring where you need X data in a spreadsheet, not an analytics dashboard. You pay per tweet or profile returned.
A RUN OF 1,000 TWEETS ON THIS SOURCE, AT 1 PER TWEET
Six columns on every row.
These come with the run and cost nothing extra. Add-ons widen the same sheet, and you pay only for the ones you switched on.
| Type | Handle | Followers | Content | Likes | Date |
|---|---|---|---|---|---|
| profile | @outboundlab | 18,400 | B2B outbound experiments, weekly | · | · |
| tweet | @outboundlab | · | Our reply rate doubled after we cut the intro line. | 612 | 2026-04-26 |
| tweet | @outboundlab | · | Cold email is not dead, your list is. | 1,940 | 2026-04-19 |
| profile | @indiefounders | 31,200 | Building in public, no fluff | · | · |
Say what you want. Read the price first.
Everything else is a ceiling or a filter. The estimate moves with the numbers you type, so the run never surprises you at the end.
The Twitter scraper takes a list of X inputs, profile URLs, @handles or individual tweet URLs, and returns structured data for each. No login or account connection is needed; it reads the public side of X the way any visitor would.
For a profile it returns the display name, bio, follower and following counts, location and verified status. For tweets it returns the text, the post date and the engagement counts, replies, reposts and likes, so you can see not just what an account said but how it landed.
The result is a dataset instead of a feed. A list of prospects or competitor accounts becomes rows you can filter by follower size, scan for talking points, or sort by engagement to find the posts that actually got traction.
Scraped as data, X becomes a research layer rather than a feed to scroll. A list of prospect handles, exported with bios and recent tweets, lets you spot the talking points worth opening with and skip the accounts that are inactive or off-topic. Sorting tweets by engagement surfaces the posts an audience actually cared about, which is useful both for understanding a competitor message and for finding the threads where potential customers already gather. Because the scraper reads the public side of X without a login, there is no account to connect and no enterprise contract to sign, the same data the platform shows every visitor, simply collected into a file you can work with.
The Twitter scraper fetches the public version of each profile or tweet and reads the data X exposes without authentication. It does not log in or use account credentials, so there is nothing to connect and no session to maintain.
Every run is live, so follower counts and engagement numbers are current as of the job. Requests route through rotating residential proxies and are paced to look like ordinary browsing, which keeps a longer list of accounts returning complete results.
Charged per delivered row. If the source holds fewer than you asked for, the rest of the credits go back to your balance the second the run ends.
One thousand tweets, itemised.
One line, because this source has nothing bundled on top. You pay the rate times the rows the run actually delivered.
| Line | Rate | Units | Credits |
|---|---|---|---|
| 1 / tweet | 1,000 tweets | 1,000 | |
| 1,000 tweets | 1 / tweet | 1,000 credits | $1.00 |
$0.001 PER FINISHED TWEET · ONLY DELIVERED ROWS ARE BILLED
What people point it at.
Four ways this source is used today. Every one of them is the same run, the same export and the same credit pool.
- Outbound teams researching what a target prospect posts about publicly to find a relevant angle.
- Brand monitors tracking mentions and competitor accounts without an enterprise data contract.
- Lead researchers scraping who replied to a competitor’s announcement to find warm prospects.
- Analysts measuring which of an account’s posts earned the most engagement over a period.
The rest of the social stack.
Same credit pool, same export. Chain the output of one run into the next without paying for the list twice.
Asked before the first run.
Short answers, no accordion to click through. If something is still missing, the help pages go deeper.
Do I need to connect an X account?
No. The Twitter scraper reads the public side of X without any login, so there is no account to connect, no password to store and no session to keep alive.
How many tweets does it return per profile?
For a profile input you set how many recent tweets to pull, and the scraper returns up to that number with full engagement counts. Direct tweet URLs return that single tweet.
What engagement data is included?
Each tweet row includes its reply, repost and like counts alongside the text and date, so you can sort an account’s posts by how much traction they earned.
How do results export?
Results download as a CSV with profiles and tweets in clearly typed rows, so you can filter by follower size or sort tweets by engagement in any spreadsheet.