Exploring AI-Powered API Testing with the Keploy Chrome Extension

GAURANG NANDA — Sat, 28 Jun 2025 04:38:04 +0000

🔍 Background
As a developer, I’ve often found manual API testing to be repetitive, error-prone, and slow. Writing and updating test cases for every endpoint change can feel like a never-ending task. To streamline this, I tried the Keploy Chrome Extension, a tool that uses AI to generate test cases automatically based on real-world API traffic.

🌐 Websites I Tested
Swiggy.com
I tested Swiggy’s API calls for restaurant listings and dynamic menu fetches. These endpoints are triggered when a user selects a location or clicks on a restaurant.

OpenWeatherMap.org
I interacted with the site’s weather forecast features and captured API calls for current weather, hourly forecasts, and location-based data.

🔧 My Experience with Keploy
Using the Chrome extension was surprisingly easy:

I opened the websites and enabled the Network tab in Chrome DevTools.

After performing basic interactions, I launched the Keploy Chrome Extension.

It automatically detected and recorded API calls as I used the websites.

Within seconds, Keploy generated test cases for those requests—including request/response payloads and headers.

It was fascinating to watch the tool generate real, runnable test cases without needing me to write a single line of test code.

💡 Key Learnings
I got hands-on experience in understanding how web apps use APIs behind the scenes.

The Keploy extension helped me visualize and capture live API traffic.

I realized that most modern sites are highly dynamic, and testing just one interaction can cover multiple API endpoints.

⚖️ Manual vs. AI-Based Testing
Aspect Manual API Testing Keploy AI-Based Testing
Setup time Long (auth, headers, mock data) None – captures live traffic
Coverage Often partial or assumed Based on real usage = full
Speed Slow and repetitive Fast and automatic
Edge case detection Easily missed Automatically included

🚀 What Excited Me Most
Zero setup: I didn't have to define routes, headers, or payloads.

Real coverage: The tests are based on real traffic, not hypothetical use.

Time-saving: It took under 10 minutes to generate meaningful tests from 2 sites.

Potential for automation: I can now plug this into a CI/CD pipeline for continuous quality checks.

🔚 Conclusion
The Keploy Chrome Extension gave me a glimpse into the future of AI-powered testing—fast, intuitive, and incredibly useful. Moving from manual to automated API testing not only boosted efficiency but gave me better confidence in the reliability of the systems I interact with. I’m excited to integrate this into my own projects and explore how far I can push AI in my developer workflow.

DEV Community: GAURANG NANDA

Exploring AI-Powered API Testing with the Keploy Chrome Extension