Best API Mocking Software - Page 2

HTTPeep

HTTPeep is an HTTP/HTTPS debugger and programmable proxy that lets you intercept, modify, route, and mock traffic with a composable rule engine. Set breakpoints on requests and responses, rewrite headers and bodies, throttle networks, and map traffic to local or remote services. Use file-based rules under version control to share templates across teams, and run the same features from a full terminal UI and CLI for remote workflows

MockAPI

MockAPI lets users mock up APIs, generate custom data, and perform operations on it using RESTful interface.

Mocki

Mockko

PinusX Webhooks

Test webhooks instantly without signup. Get unique HTTPS URLs that capture every request. Inspect headers, format JSON payloads, and debug integrations in real-time. Features: • Instant unique webhook URLs • Real-time request inspection • Auto-formatted JSON payloads • Copy as cURL • Free tier forever

Simceptor

Simceptor is a cloud-hosted mock API server that enables developers to create and test REST, SOAP, and WSDL endpoints without backend coding. The no-code interface allows instant setup of mock servers, eliminating hardcoded JSON files. [redacted]. The platform includes [redacted]. Latency simulation tests UI loading states, while custom headers support CORS and authentication scenarios. An interactive API Playground enables direct endpoint testing within the browser. The Stateful Scenario Canvas provides visual design of multi-step flows with session management backed by Redis. Webhook forwarding simulates callbacks and event-driven architectures. Model Context Protocol integration connects AI tools like Cursor and Claude for mock creation. An AI Issue Tracker flags and automates fixes for identified bugs. The platform supports importing Swagger, OpenAPI, and Postman collections to auto-generate mock endpoints from existing schemas.

Sparrow

Sparrow is an AI-powered API testing platform designed to streamline and automate testing for developers, QA engineers, and DevOps teams. It supports REST and GraphQL APIs, integrates seamlessly with Git for version control, and offers self-hosting for secure infrastructure management. Key features include AI-driven test automation, real-time collaboration, mock servers, automated data generation, and environment vaults. With new enhancements like active sync with Swagger/OpenAPI, AI-powered test flow completion, and improved team collaboration, Sparrow helps teams test faster, reduce manual errors, and scale efficiently—making API testing seamless, intelligent, and collaborative.

Specmatic

Specmatic is a visual AI-ready API testing and governance platform that transforms API specifications into executable contracts, enabling development teams to validate API implementations, perform service virtualisation, and monitor API ecosystem health without writing code. This comprehensive solution addresses the critical challenges faced by organisations using microservices architectures, where API compatibility issues often emerge late in the development cycle. Built on the open-source Specmatic engine, the platform serves software development teams, QA engineers, API architects, and engineering managers who need to ensure reliable API integrations whilst maintaining development velocity. The platform consists of two integrated components: Studio provides a visual, no-code interface for contract testing, API mocking, and specification management, whilst Insights delivers organisation-wide API governance through dependency visualisation and adoption analytics. Teams can either directly access the underlying Specmatic engine via CLI for programmatic control or leverage Studio's graphical interface for collaborative workflows. Key Features and Benefits: • Visual Contract Testing: Automatically generates and executes comprehensive API tests from specifications (OpenAPI, AsyncAPI, GraphQL, gRPC, WSDL, Arazzo) without requiring code, enabling cross-functional teams to participate in API quality assurance • Intelligent Service Virtualisation: Creates realistic API mocks based on specifications with fault injection capabilities, allowing teams to test against dependencies and simulate error conditions like timeouts and service failures • Backward Compatibility Validation: Integrates with Pull/Merge Request workflows to identify breaking changes before code implementation, preventing integration issues from reaching production environments • Multi-Protocol Support: Supports diverse API specifications and communication protocols including HTTP (REST), Kafka, JMS, Google Pub/Sub, SOAP, JDBC, RESP (Redis), and Avro in a language-agnostic manner • Organisational API Governance: Provides service mesh visualisation, contract adoption tracking, and integration health monitoring through centralised dashboards that aggregate data from multiple development environments The platform enables teams to practice contract-driven development by treating API specifications as living, executable documents rather than static documentation. This approach reduces dependency on integration testing, accelerates parallel development of services, and provides early detection of compatibility issues. Development teams can work independently whilst maintaining API contract compliance, significantly reducing time-to-market for new features and services. Specmatic Studio & Insights integrates seamlessly with existing CI/CD pipelines and development workflows, making it suitable for organisations of varying sizes that need to scale their API testing and governance practices without increasing technical complexity or resource requirements.

Speedscale

Speedscale captures real production HTTP, gRPC, and SQL traffic inside your own Kubernetes cluster and turns it into a closed AI-agent loop: discover → spec → triage → reproduce → validate → PR. Nothing leaves your environment. Bring Your Own Everything. The capture agent, traffic store, and replay engine run as a Kubernetes operator in your cloud — not ours. You bring your apps, your storage, your AI models (private Anthropic, self-hosted Llama, in-house — whatever your compliance posture allows), and your governance controls. Speedscale orchestrates the loop without locking you to any cloud, model vendor, or storage tier. The closed AI-agent loop. When a production failure occurs, the eBPF capture agent records the exact request — full payload, headers, SQL statements, all dependent traffic. An AI triage agent specs the problem, classifies it, and routes it. A reproduction agent replays the identical traffic against your current codebase in a non-production environment to confirm the failure. A validation agent verifies the fix before the PR is opened. Human review is optional at every stage — run fully autonomous or fully human-gated. Same product, different governance. proxymock — the developer entry point. Teams start with proxymock, a free CLI that stands in for downstream dependencies using recorded production responses. AI coding agents (Claude Code, Cursor, GitHub Copilot) query captured production traffic through the MCP integration, giving them real-world context — actual failed requests from your environment — instead of synthetic test data. Enterprise data residency. For regulated industries — financial services, healthcare, payments, regulated retail — production API payloads cannot leave the enterprise environment. Speedscale's BYOC architecture is the only production-traffic-capture approach that satisfies this constraint without sacrificing the payload fidelity needed for AI-driven bug reproduction. Speedscale is used by engineering teams at Home Depot, IHG (InterContinental Hotels Group), FLYR, Cimpress/Vistaprint, Navitaire (an Amadeus subsidiary), and Ascension Health.

Traffic Parrot

Traffic Parrot provides API and service simulation, service virtualization and API mocking software and consulting services to both startups and established e-commerce and financial institutions.

Zunoy MockAPI

Zunoy MockAPI is an API mocking and simulation tool that helps developers test, prototype, and validate API-based workflows without relying on backend systems or production services. It belongs to the API Development and Testing software category and is designed for frontend developers, QA engineers, DevOps teams, and product managers who need to simulate real-world API behavior during the software development lifecycle. With Zunoy MockAPI, users can instantly create and deploy custom RESTful endpoints that return static or dynamic responses. This enables teams to work in parallel—building UI components, integrating services, or performing automated testing—before the actual APIs are ready. It is especially useful in scenarios involving microservices, third-party APIs, or unstable backend environments. Zunoy MockAPI offers a hosted, web-based interface, making it easy to configure and manage mocks without setting up local environments or writing code. It supports JSON responses, custom status codes, headers, latency simulation, and CORS configuration to replicate real-world API behavior. Key features of Zunoy MockAPI include: Instant API Mocking: Create REST API endpoints with custom paths, methods, and response structures in seconds. Dynamic Responses: Customize responses using variables, random data, and conditional logic to mimic realistic API behavior. Latency and Error Simulation: Add delays, timeouts, and custom error codes to test how your frontend or client handles network issues. No-code Configuration: Use an intuitive web UI to set up mocks—no need to install software or write scripts. Team Collaboration: Share mock APIs via public or private URLs to support collaboration across distributed teams. Zunoy MockAPI helps teams reduce development dependencies, improve testing coverage, and accelerate time-to-market by simulating APIs early in the development process.