SerpApi VS textToolkit.dev

SerpApi's answer

We provide more search engines under one subscription.

textToolkit.dev's answer:

Most free text-tool sites are cluttered with ads, slow, or send your text to a server to process it. textToolkit is fast, clean, works well on mobile, supports dark mode, and processes everything locally in the browser — so there's no privacy tradeoff and no waiting on a server round-trip. It's also actively growing, with new tools added regularly based on real user needs.

SerpApi's answer

Developers/Companies who need data from search engines.

textToolkit.dev's answer:

Writers and bloggers who need to fix formatting or capitalization; developers who need to convert variable naming conventions (camelCase, snake_case) or clean up data; students working on essays and citations; and social media/content marketers who need character counts, slugs, or quick text formatting for platforms like Instagram and Twitter/X.

SerpApi's answer

Ruby on Rails and MongoDB

textToolkit.dev's answer:

Astro (for a fast, mostly-static site architecture) and Tailwind CSS for styling, with vanilla JavaScript powering the client-side text processing in each tool. No backend or database is required since all processing happens in the browser.

SerpApi's answer

We're the first web scraping company that focus on scraping search engines.

textToolkit.dev's answer:

textToolkit runs entirely in the browser — no text is ever uploaded, stored, or sent to a server. Every conversion, cleanup, and analysis happens client-side, making it a genuinely private option for working with sensitive content. It also covers a wide range of tools (case conversion, text cleanup, analysis, and fun utilities) in one consistent, fast interface, rather than requiring separate bookmarks for each task.

SerpApi's answer

Back in 2017, Julien Khaleghy, the founder of SerpApi, built an iOS app that can analyze data from a picture. iOS didn't have a proper machine learning framework back then. It was challenging: iPhones' RAM were limited, no GPU or no dedicated chip acceleration were available, using only CPU was painfully slow, and compiling/porting C code from machine learning framework like Tensorflow or Caffe to iOS wasn't straightforward. Oddly, all of this wasn't the most difficult part of this project. Collecting images from Google Images was.

In these projects, 80% of his time ended up being spent on scraping and parsing Google Images. And maybe only 20% on actual machine learning model training, UI design of the actual apps, and iOS programming. This is how SerpApi was born.

textToolkit.dev's answer:

textToolkit started as a simple case converter built to solve a common, everyday annoyance — reformatting text between different capitalization styles. It quickly grew into a broader toolkit as it became clear the same problem existed across dozens of small text tasks: removing extra spaces, cleaning up pasted HTML, counting characters for a tweet, generating a URL slug. The goal became building one fast, ad-light, privacy-respecting home for all of these small but frequent tasks.

SerpApi's answer

• Airbnb
• Nvidia
• Meta
• Shopify
• Grubhub
• and more!

textToolkit.dev's answer:

textToolkit is newly launched and used by individual writers, students, and developers rather than enterprise customers at this stage. As a free, sign-up-free tool, usage is anonymous and not tracked by company or account, so no user data is available to name specific customers.