Keploy

What is Keploy?

Keploy is an open source, AI-powered tool for developers that helps generate test cases and create mocks/stubs for unit, integration, and API testing. Its core purpose is to support repeatable automated testing by capturing real API interactions and using them to produce stable tests.

Keploy focuses on reliability and coverage by recording API traffic and replaying it in a CI-friendly, isolated environment. The result is a workflow intended to reduce manual effort in building test cases and maintaining mocks.

Key Features

Record API traffic from real requests: Captures interactions from actual API calls so test inputs can reflect real usage patterns.
Replay into a sandboxed test environment: Replays recorded traffic to run tests in isolation, supporting consistent runs in CI.
Generate AI-assisted test cases: Uses AI to generate tests based on observed behavior, aiming to reduce manual test authoring.
Create mocks/stubs for API and integration testing: Produces mocked responses to decouple tests from external dependencies.
Coverage reporting for testing progress: Includes coverage reporting to help you track and improve how much of your codebase is exercised.
Deterministic test runs: Emphasizes fast, deterministic replay behavior intended to keep tests stable.

How to Use Keploy

Start by recording the API traffic you want to test, capturing the interactions your application makes.
Use the recorded traffic to generate tests and mocks/stubs, so you have repeatable test inputs without relying on live dependencies.
Replay the recorded behavior in your pipeline (e.g., CI) to run tests in an isolated sandbox.
Review coverage reporting to understand what’s already exercised and decide what additional endpoints or scenarios to record next.

Use Cases

API integration testing with reduced dependency management: Record interactions from an upstream service and use the resulting mocks/stubs to run integration tests without calling the real service.
Stabilizing tests in CI: Replay recorded API traffic into an isolated sandbox so test outcomes depend on deterministic inputs rather than fluctuating external conditions.
Improving test coverage efficiently: Use coverage reporting to identify gaps, then record additional endpoints or flows and regenerate tests to expand coverage.
Unit and integration test acceleration: Generate tests and mocks from real API behavior so developers can focus on refining assertions and edge cases rather than starting from scratch.
Creating repeatable test scenarios from real traffic: Capture real request/response sequences and reuse them to ensure the same behaviors are validated across runs.

FAQ

Is Keploy open source?

Yes. The site describes Keploy as an open source tool.

What kinds of tests does Keploy support?

Keploy is positioned for unit, integration, and API testing, including workflows that involve recording and replaying API traffic.

How does Keploy help with test reliability?

Keploy emphasizes stable, deterministic test runs by replaying recorded API traffic into an isolated sandbox for CI.

Does Keploy generate mocks or stubs?

Yes. The site describes Keploy as generating mocks/stubs for testing based on recorded behavior.

Does Keploy provide coverage visibility?

Yes. The page references coverage reporting to help track testing coverage.

Alternatives

API testing tools with mocking/stubbing (manual or scripted): Tools in this category help you stub endpoints for tests, but typically require more manual setup of mock responses and test cases.
Traditional unit/integration testing frameworks with fixtures: Frameworks can cover unit and integration testing, but they don’t inherently provide the record-and-replay workflow for generating tests and mocks from real API traffic.
Contract testing approaches (schema-based validation): Contract testing can validate API expectations, but it may not directly provide the same record/replay mechanism for generating deterministic mocks and tests from live traffic.
End-to-end testing frameworks: E2E tools exercise full flows, but they often trade off speed and isolation compared with focused unit/integration/API tests using mocks and replay.