Open-source, AI-powered testing agent that automatically generates test cases, dependency mocks, and production-like sandboxes from real user traffic using eBPF. Helps developers achieve 90% test coverage in minutes with zero code changes.
Keploy is an open-source AI-powered API testing agent that automatically generates test cases and dependency mocks from real user traffic using eBPF, achieving up to 90% test coverage in minutes with zero code changes â and it's completely free for the open-source version. It's built for backend developers, QA engineers, and DevOps teams who want to eliminate the manual toil of writing unit and integration tests while ensuring production-like reliability in CI pipelines.
Based on our analysis of 870+ AI tools in the directory, Keploy stands out in the developer testing category by using record-and-replay methodology powered by eBPF kernel-level instrumentation. Instead of writing tests by hand, developers simply run their application through Keploy, which captures real API calls along with their database queries, Redis calls, and third-party service interactions. These captured traffic samples are then converted into deterministic test cases with auto-generated mocks, creating an isolated sandbox environment that can be replayed in CI for regression testing. The project has earned 15,600+ GitHub stars, surpassed 1.2M+ downloads, and generated over 200M+ mocks across its user base â a strong indicator of real-world adoption.
Compared to traditional testing frameworks like Jest, Pytest, or Postman, Keploy removes the need to write test code manually and handles mocking automatically. While tools like Postman focus on API collection testing and Jest requires developers to author assertions, Keploy's AI-powered approach auto-generates both tests and mocks from production-like traffic. It also provides coverage reporting and performance testing in the same workflow. The tool supports Go, Python, Java, Node.js, and other major backend languages, and includes a cloud offering for teams that need centralized test management, collaboration, and enterprise-grade deployment on top of the open-source core.
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Keploy uses eBPF to capture API traffic at the Linux kernel level, intercepting HTTP calls and all downstream dependency interactions without requiring code instrumentation. This approach is less invasive than SDK-based solutions and works across languages, making it a powerful foundation for language-agnostic test generation.
The platform automatically converts captured API traffic into deterministic test cases, achieving up to 90% coverage in minutes. Over 200M+ mocks have been generated across its user base, showing that the AI-driven generation engine handles diverse real-world traffic patterns at scale.
Keploy records interactions with databases, Redis, message queues, and third-party APIs, then generates mocks that replay these dependencies deterministically in CI. This eliminates the manual work of writing and maintaining mocks, which is often the most tedious part of integration testing.
Recorded tests and mocks can be replayed inside isolated sandbox environments during CI runs, providing production-like test conditions without needing live dependencies. This delivers fast, deterministic regression testing that catches integration issues before deployment.
Beyond generating tests, Keploy provides detailed coverage reporting and performance testing capabilities in the same workflow. Developers get visibility into both what's tested and how their APIs perform, making it a more complete solution than single-purpose testing tools.
Free
Custom pricing (estimated $30â$80/user/month based on comparable enterprise API testing platforms)
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In early 2026, Keploy released v2.4 with a revamped AI test-generation engine featuring improved deduplication of captured test cases and smarter assertion inference for complex JSON response bodies. The February 2026 release introduced native contract testing support, allowing teams to validate API schemas against recorded traffic automatically. GitHub stars surpassed 16k in Q1 2026, and the project shipped Docker-native recording mode (eliminating the need for root-level eBPF permissions in containerized environments). The cloud platform added a team dashboard with historical coverage trend tracking and Slack-integrated test failure notifications.
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