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Keploy

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.

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Overview

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 — 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 — 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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Key Features

eBPF-Powered Traffic Recording+

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.

AI-Powered Test Case 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.

Automatic Dependency Mocking+

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.

CI-Ready Sandbox Replay+

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.

Coverage & Performance Reporting+

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.

Pricing Plans

Open Source

Free

  • ✓Full eBPF-powered traffic recording
  • ✓Automatic test case and mock generation
  • ✓Self-hosted deployment
  • ✓CI/CD integration
  • ✓Multi-language support (Go, Python, Java, Node.js)
  • ✓Community support via GitHub (15.6k+ stars)

Cloud / Enterprise

Custom pricing (estimated $30–$80/user/month based on comparable enterprise API testing platforms)

  • ✓Centralized test management
  • ✓Team collaboration features
  • ✓Managed deployment
  • ✓Advanced coverage & performance reporting
  • ✓Priority enterprise support
  • ✓SSO and enterprise security
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Best Use Cases

đŸŽ¯

Backend teams migrating legacy services who need broad regression test coverage quickly without rewriting test suites from scratch

⚡

Microservices teams wanting isolated, deterministic sandbox replays in CI to catch regressions before they hit production

🔧

DevOps engineers automating API testing in CI/CD pipelines using recorded traffic and auto-generated mocks

🚀

QA teams validating dependency interactions (databases, Redis, third-party APIs) without manually authoring mocks

💡

Startups and open-source projects that need high test coverage fast but lack dedicated QA resources or budget

🔄

Enterprise platform teams benchmarking API performance and coverage across Go, Python, Java, and Node.js services

Limitations & What It Can't Do

We believe in transparent reviews. Here's what Keploy doesn't handle well:

  • ⚠Requires Linux kernel with eBPF support for full functionality — limited on native Windows and some macOS setups
  • ⚠Only as good as the captured traffic — rarely-triggered edge cases won't appear in auto-generated tests
  • ⚠Not suited for frontend, UI, or browser-based end-to-end testing workflows
  • ⚠Enterprise/cloud pricing requires a demo booking and is not publicly transparent
  • ⚠Traffic-based test generation means sensitive data in captured requests must be carefully handled or redacted

Pros & Cons

✓ Pros

  • ✓Completely free and open-source with 15,600+ GitHub stars and 1.2M+ downloads, proving strong community trust
  • ✓Achieves up to 90% test coverage within 2 minutes without requiring any code changes to the application
  • ✓Uses eBPF for kernel-level traffic capture, which is more accurate and less invasive than SDK-based instrumentation
  • ✓Auto-generates dependency mocks (200M+ mocks created), eliminating manual mock authoring for databases and external services
  • ✓Supports multiple backend languages including Go, Python, Java, and Node.js, making it broadly applicable
  • ✓Deterministic replay in CI creates production-like sandboxes for reliable regression testing

✗ Cons

  • ✗eBPF requires Linux kernel support, limiting native use on Windows and some macOS configurations
  • ✗Primarily focused on backend API testing — not suited for frontend UI or end-to-end browser testing
  • ✗Record-and-replay approach may miss edge cases that don't appear in captured production traffic
  • ✗Learning curve for teams unfamiliar with eBPF concepts and traffic-based test generation
  • ✗Cloud/enterprise pricing is not publicly listed, requiring a demo booking for teams needing managed features

Frequently Asked Questions

How does Keploy achieve 90% test coverage in 2 minutes without code changes?+

Keploy uses eBPF (extended Berkeley Packet Filter) to capture API traffic at the Linux kernel level while your application runs normally. As real user requests flow through your backend, Keploy records the HTTP calls along with all downstream dependency interactions like database queries, Redis calls, and external API requests. These captured interactions are then automatically converted into test cases with auto-generated mocks, so running your app through typical usage for just a couple of minutes can produce broad coverage without writing a single line of test code.

Is Keploy actually free, or are there hidden costs?+

The core Keploy testing agent is fully open-source and free to use, with over 1.2M+ downloads and 15,600+ GitHub stars backing it up. You can self-host it, integrate it into your CI/CD pipelines, and generate unlimited tests and mocks at no cost. Keploy also offers a cloud/enterprise tier for teams that need centralized test management, collaboration features, and managed deployment — pricing for that tier requires booking a demo through their website.

What languages and frameworks does Keploy support?+

Keploy supports major backend languages including Go, Python, Java, and Node.js, along with their popular frameworks. Because it uses eBPF to intercept traffic at the system level rather than instrumenting application code, it's largely language-agnostic at the capture layer. This means adding new language support primarily involves handling framework-specific serialization rather than rewriting the core engine, and the project regularly adds new integrations based on community demand.

How does Keploy compare to Postman or traditional testing frameworks like Jest?+

Postman is primarily a manual API collection and testing tool — you author requests and assertions yourself. Jest and similar unit testing frameworks also require developers to write test logic by hand. Keploy is fundamentally different: it generates both test cases AND mocks automatically from real traffic, then replays them deterministically in CI. Based on our analysis of 870+ AI tools, Keploy occupies a unique niche by combining AI-powered test generation with eBPF traffic capture, which most traditional tools don't offer.

Can Keploy be used in production environments safely?+

Keploy is designed to capture traffic in staging or dev-like environments and replay in CI sandboxes, not to run as a production dependency. The recording phase is passive and uses eBPF, so it has minimal overhead and doesn't modify application behavior. Teams typically record traffic from staging environments that mirror production, then use those captured tests in CI pipelines for regression testing — keeping the production runtime untouched while still benefiting from realistic test scenarios.
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What's New in 2026

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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