Top 11 API Tools for Testing in 2026

APIs (Application Programming Interfaces) power everything from mobile apps and SaaS platforms to AI agents and IoT devices. According to industry reports, API traffic now accounts for over 71% of web interactions. This means that if your APIs aren’t reliable and secure, nothing built on top of them will be either.

API testing is the practice that keeps those stakes in check. It validates that your APIs behave correctly, perform under pressure, and resist attacks before they reach your users. But the tooling options have shifted considerably heading into 2026. AI agents can now run security scans, generate test cases, and fix vulnerabilities through MCP (Model Context Protocol) server connections to testing platforms. Combined with tighter CI/CD alignment and self-healing test suites, the bar for what a “good” API testing tool looks like has moved significantly.

This article covers the key properties to look for in an API testing tool, the top 11 options available in 2026, and practical guidance for choosing the right fit. If you’re looking for a broader view of testing methodologies and how to select a framework, check out our companion guide on API testing frameworks.

Understanding API Testing

API testing verifies that your APIs work correctly, perform under pressure, and resist attacks. You send requests to API endpoints, analyze the responses, and validate behavior against the contract your API defines. 

Although manual testing is still required in development, in practice, most DevOps and development teams lean heavily on automated API testing as part of their continuous testing strategy. The biggest advantage is catching issues early in the development lifecycle, often before the UI is even built. 

Unreliable responses, slow performance under load, broken authentication, data exposure, and injection vulnerabilities all surface faster with the right tooling. API testing tools make this process scalable so you can maintain high standards for software quality and security as your application grows.

Types of API Tests

Different testing needs call for different tools, so understanding the main categories helps you evaluate which tools on this list match your priorities.

Functional Testing

Functional testing verifies that each endpoint returns the correct data, handles edge cases, and behaves as specified across all supported request types. This is the foundation. Tools like Postman, REST Assured, and Karate DSL are built around this category.

Load and Performance Testing

Load and performance testing assess how your API holds up when traffic spikes, measuring speed, stability, and scalability under realistic conditions. Apache JMeter is the go-to here, and Karate DSL can double as a load testing tool through its Gatling integration.

Security Testing

With a different scope than functional and performance testing, software security testing focuses on finding vulnerabilities that attackers could exploit: unauthorized access, data exposure, and injection flaws. For teams in regulated environments (PCI DSS scope, HIPAA, SOC2), continuous API security testing is increasingly expected. StackHawk is purpose-built for this, running DAST scans directly in CI/CD.

Contract Testing

Contract testing verifies that API providers and consumers adhere to a shared agreement, catching integration issues before they reach staging or production. Tools like Pact and Specmatic have become staples in microservices testing pipelines, and interest in this category has surged as architectures have grown more complex.

These are the main categories that should drive your tool selection.

Key Features to Look for in an API Testing Tool

A good API testing tool lets you create, execute, and manage tests efficiently while fitting into your existing development workflow. Here’s what to look for.

Ease of Use

The tool should be easy to pick up, with support for both technical and non-technical users. In 2026, many tools offer no-code or low-code options (Katalon, Postman) alongside scripting capabilities (REST Assured, Karate DSL) to serve teams with varying levels of expertise.

Wide Protocol Support

Look for support across REST, SOAP, GraphQL, and gRPC, as well as common data formats like JSON and XML. With the rise of event-driven architectures using async APIs, webhooks, and WebSockets, protocol breadth has become an even more important differentiator.

Test Features

Flexible test creation (visual editors, scripting, AI-assisted generation), reusable test components, data-driven testing with CSV files or mock data, and CI/CD pipeline integration are all table stakes. The tool should also support the API test types discussed above: functional, security, and performance testing. Strong test data management and mock resources for simulating different conditions matter too.

Assertions and Validation

The tool should provide strong mechanisms for validating API responses: status codes, data types, response schemas, and expected behavior. This ensures your API maintains its contract as it evolves.

Reporting and Analysis

Look for detailed test reports, logs, and visualizations that make it clear what failed, why, and what to fix first.

Collaboration

Sharing tests, results, and test environments among team members matters, particularly for distributed teams. Workspaces and collections with version control (like Postman’s or Bruno’s Git-native approach) help a lot here.

Monitoring and Alerting

Continuous API monitoring with real-time alerts for issues and anomalies keeps you aware of problems in production before your users notice them.

Customizability and Extensibility

The tool should grow with your product through plugins, scripts, or custom code. In 2026, the most forward-looking tools also expose MCP servers that connect directly to AI coding assistants like Cursor, Claude Code, and Windsurf. This means developers can trigger scans, query test results, and generate configurations through natural language rather than clicking through a UI or writing boilerplate YAML.

Now, onto the tools themselves.

Top 11 API Testing Tools for 2026

There are a lot of capable tools on the market in 2026. Here are eleven that stand out, each with different strengths:

Tool	Primary Use	Open Source	CI/CD Native	Best For
StackHawk	Security Testing	Commercial	Yes	Dev & AppSec teams wanting automated API security testing in CI/CD and AI coding workflows
Postman	Functional Testing	Free + Paid	Yes	Teams needing a single platform for API development, testing, and collaboration
SoapUI	Functional Testing	Free + Paid	Via ReadyAPI	Teams with heavy SOAP API use or needing deep scripted assertion customization
Apache JMeter	Performance Testing	Open Source	Yes	Teams needing load and performance testing on a budget
REST Assured	Functional Testing	Open Source	Yes	Java teams wanting code-first REST tests that live alongside application code
Katalon Studio	Functional Testing	Free + Paid	Yes	Teams needing unified API, web, and mobile testing with low-code accessibility
Bruno	API Client	Open Source	Yes	Developer teams wanting Git-native API collections without cloud lock-in
Karate DSL	Functional Testing	Open Source	Yes	Teams wanting one framework for API testing, mocking, and performance testing
APITect	Design-First	Commercial	Yes	Teams that want contract-based API development to prevent integration failures
Apigee	API Management	Commercial	Partial	Enterprise orgs needing API management, governance, and monitoring in regulated environments
Swagger	Design & Docs	Free + Paid	Via integrations	Teams whose testing strategy is tightly coupled with API documentation and OpenAPI workflows

Selecting the right tool depends on your project requirements, team expertise, and specific testing needs. Let’s look at each one in detail.

StackHawk

StackHawk is a DAST platform purpose-built for API security testing. It runs directly in your CI/CD pipelines and surfaces vulnerabilities before code reaches production. Unlike traditional scanners that bolt security on after the fact, StackHawk is designed around the developer workflow, giving you enough context to understand and fix issues without looping in a separate security team.

Key features:

• Scans APIs for vulnerabilities like SQL injection, XSS, and insecure configurations across REST, SOAP, GraphQL, and gRPC. Smart Crawl analyzes your OpenAPI specs to build deterministic test flows that simulate real user behavior, reducing manual configuration.
• Business Logic Testing (BLT) automates multi-user authorization testing using configurable profiles (admin, member, guest). It catches BOLA, BFLA, and privilege escalation flaws from the OWASP API Security Top 10, with full request/response evidence for each finding.
• Source code-based API discovery integrates with GitHub and GitLab to map your full attack surface, including undocumented and shadow APIs. It generates OpenAPI specs and detects sensitive data patterns (PII, PCI, PHI) automatically.
• StackHawk’s MCP server brings DAST into AI coding assistants like Cursor, Claude Code, and Windsurf. Developers can trigger scans, review findings, apply fixes, and rescan to verify remediation without leaving their editor.
• Findings route to Jira, Slack, and pull request comments, and integrate with Semgrep for correlating DAST and SAST results into unified remediation workflows.

Best for: Development and AppSec teams that want automated API security testing, including business logic and authorization testing, embedded in CI/CD and AI-assisted coding workflows. See pricing.

Postman

Postman started as a REST API client but now positions itself as a full lifecycle API management platform with significant AI capabilities. Its Collections and Workspaces remain the core of how teams organize, share, and automate API testing workflows, and the platform has added agentic features that let developers interact with their APIs using natural language.

Key features:

• Collections and Workspaces provide controlled access, environment management, and built-in version control for collaborative API testing.
• Agent Mode uses AI to turn natural language commands into executable API actions, handling tasks like designing, testing, documenting, and monitoring APIs.
• The AI Agent Builder integrates with MCP, connecting large language models to your API infrastructure. Developers can create multi-step agents to automate common API tasks and test LLM-powered endpoints.
• Mock servers allow developers to simulate APIs before actual development, supporting rapid prototyping and functional API testing of endpoints.
• The new API Catalog provides a centralized view of your API portfolio, bringing together specs, collections, test execution, CI/CD activity, and production observability.
• Expanded protocol support covers GraphQL, gRPC, WebSocket, Socket.IO, and MQTT alongside traditional REST and SOAP APIs. Postman can also act as an MCP client, connecting AI agents directly to your API workflows.

Best for: Teams that need a single platform for API development, testing, and collaboration across the entire API lifecycle, especially those adopting AI-assisted workflows.

SoapUI

SoapUI is an open-source API testing tool with deep strengths in testing SOAP APIs, REST, and web services. It’s been around for years, and its Groovy scripting engine gives it a level of assertion flexibility that few other tools match. For teams that need more advanced features, SmartBear’s commercial tier, ReadyAPI, adds AI-powered test generation and deeper CI/CD integration on top of the same SoapUI engine.

Key features:

• A user-friendly graphical interface with drag-and-drop capabilities for building test flows.
• Automated functional, regression, and load tests that cover the full API testing process.
• Powerful assertion capabilities using Groovy scripting natively, with support for libraries like AssertJ for more specialized validation.
• Built-in mocking for simulating API behavior during development.
• Recent updates added GraphQL support and Docker-based test execution, keeping SoapUI current with modern API architectures.

Best for: Teams that rely heavily on SOAP APIs or need deep assertion customization through scripting, and teams already using SmartBear tools.

Apache JMeter

Apache JMeter is an open-source tool built for load and performance testing of REST and SOAP APIs. It simulates heavy traffic under a wide range of conditions, making it the default choice for teams that need to know how their APIs behave under pressure. JMeter has been around for over two decades, and its cross-platform nature means it runs anywhere Java does.

Key features:

• Simulates thousands of concurrent users to stress-test your APIs across complex scenarios.
• Supports CSV files as a test data source, making data-driven API testing straightforward to set up.
• Extensible through plugins for protocol support, reporting, and CI/CD integration.
• Free, open-source, and cross-platform with a large community and extensive documentation.
• Integrates with CI/CD pipelines for automated performance and load testing as part of your build process.

Best for: Teams that need dedicated API performance testing and load testing on a budget, especially those already comfortable with Java-based tooling.

REST Assured

REST Assured is the go-to Java library for automating REST API testing. Its fluent syntax makes it easy to write readable test scripts that live right alongside your application code. REST Assured integrates with the Serenity automation framework and Java testing frameworks like JUnit and TestNG, bringing powerful behavior-driven test features and reliable test automation for thorough REST API testing.

Key features:

• Expressive, fluent syntax that simplifies the creation of API test scripts and makes tests easy to read.
• Built-in support for JSON and XML parsing, handling complex API responses with minimal code.
• Mock server integration for testing against simulated API endpoints.
• Seamless integration with JUnit, TestNG, and the Serenity BDD framework for behavior-driven testing.
• Tests live in the same codebase as your application, making them easy to version, review, and maintain.

Best for: Java-centric teams that want type-safe, code-first REST API tests living alongside their application code.

Katalon Studio

Katalon Studio provides end-to-end API test automation built on top of trusted open-source solutions like Selenium and Appium. Its strength is that API tests live in the same platform as your web and mobile tests, so teams can manage their entire testing effort from one place. In 2026, Katalon stands out for its low-code approach combined with AI-assisted test generation, which makes it accessible to teams that don’t have deep programming experience.

Key features:

• Low-code test creation with pre-built API frameworks, plus support for the Java testing frameworks TestNG and JUnit for teams that prefer writing code.
• Import requests from OpenAPI, Postman, and SoapUI to get started quickly with existing API definitions.
• AI-powered self-healing tests that automatically adapt when API responses or element selectors change, reducing test maintenance overhead.
• Test recording feature that generates test scripts by capturing interactions with APIs, saving time while producing accurate test cases.
• Run large-scale data-driven tests across API, web, and mobile in a single testing platform.

Best for: Teams that need a unified testing platform covering API, web, and mobile testing with low-code accessibility and AI-assisted test maintenance.

Bruno

Bruno is an open-source API client that’s become increasingly popular in 2026, particularly with teams that want their API testing workflow to live alongside their application code. Instead of syncing collections to the cloud, Bruno stores everything as plain-text .bru files on your local filesystem. That means your API requests, test scripts, and environment configs all go straight into Git, just like the rest of your codebase.

Key features:

• Git-native by design: API collections are plain-text files that you can branch, diff, and review in pull requests alongside the code that changed the endpoint.
• Offline-first and fast, with no cloud sync dependency or account requirement to get started.
• CLI runner that executes collections from the terminal with JUnit-compatible output, making CI/CD integration straightforward.
• Environment management through local config files, giving teams full control over where their API data lives.
• Open-source with a growing community and active development.

Best for: Developer teams that want Git-native API collections treated as code, and organizations that prefer offline-first tools without cloud lock-in.

Karate DSL

Karate DSL is a domain-specific language that combines API testing, mocking, performance testing, and even UI automation in a single framework. It uses BDD (Behavior-Driven Development) syntax that requires no step definitions, meaning even non-programmers can write and maintain test cases. The framework also integrates with Gatling for performance testing, so you can reuse your functional API test suites as load tests without maintaining separate codebases.

Key features:

• BDD syntax with no step definitions required, so even non-programmers can write and maintain API tests.
• Built-in support for mocking, including mock servers, dynamic response generation, and data-driven mocking with CSV files.
• Integrates with Gatling, letting you reuse functional API test suites as load and performance tests.
• Version 1.5.0 added Playwright support for UI testing, a Java DSL for Gatling, and Java 22+ compatibility.
• Handles test creation across API and UI testing in a single framework with minimal configuration.

Best for: Teams that want a single, code-light framework covering API testing, mocking, and performance testing without stitching together multiple tools.

APITect

APITect is a design-first API lifecycle platform built around contract-based development. Rather than treating API work as an afterthought (like many testing-first tools do), it treats the API contract as the source of truth and uses it to generate documentation, validate implementations, and enable parallel frontend/backend work from the start. Teams that struggle with mismatched expectations between frontend, backend, and QA tend to find the most immediate value here.

Key features:

• Visual builders and AI assistance generate OpenAPI contracts from sample payloads or plain language, reducing the barrier to formal API design.
• Real-time contract validation continuously checks live implementations against the design spec, catching mismatches before they reach staging or production.
• API docs are auto-generated from the contract and update automatically with every design change.
• Instantly generated mock servers let frontend and backend teams work in parallel against the same contract.
• An AI test suite generator creates test cases—including edge cases and negative scenarios—directly from the contract spec.
• CI/CD integration with GitHub Actions, GitLab CI, CircleCI, and Bitbucket enforces contract compliance as part of the build process.

Best for: Technical teams and engineering leaders who want to standardize API development around an enforceable design contract and prevent integration failures before they happen, especially when teams struggle with coordination between frontend, backend, and QA. 

Apigee

Apigee is primarily an API management platform rather than a dedicated testing tool, but it earns a spot on this list because of its testing-adjacent capabilities. As Google Cloud’s full lifecycle API management offering, it provides tools for designing, building, and monitoring APIs, along with strong features for creating mock services, executing performance tests, and tracking API health in production. In 2026, Apigee added AI-powered developer tools and zero-trust security features to its platform.

Key features:

• Covers API design, testing, governance, and monitoring from a single platform.
• Strong mock service creation and management for simulating API behavior during development and testing.
• Supports compliance frameworks including PCI DSS, HIPAA, and SOC2, making it a fit for regulated industries.
• Cross-cloud API management for hybrid environments with AI-powered developer tools.
• Production monitoring and traffic analytics that provide real-time insight into API health and performance.

Best for: Enterprise organizations that need API management, governance, and monitoring alongside testing, especially those in regulated or multi-cloud environments.

Swagger

Swagger is primarily a design and documentation tool, but it enables testing through OpenAPI-driven workflows and integrations. These tools simplify the creation, sharing, and collaboration of detailed REST API documents. By supporting OpenAPI specifications, Swagger ties API development and testing workflows together around a shared spec. Some have described its approach as similar to what the RESTful API Modeling Language (RAML) aimed to achieve, but with broader industry adoption.

Key features:

• Swagger UI lets you generate interactive API documentation from your API’s OpenAPI Specification document, making it easy to test API endpoints directly from the docs.
• Third-party tools integrate with Swagger to enable the creation of mock servers and test cases based on your OpenAPI documentation.
• Supports the full OpenAPI specification for standardizing API design, documentation, and testing workflows.
• Enables collaboration between testers, product managers, and developers around a shared API definition.
• Widely adopted with a large ecosystem of compatible tools and integrations.

Best for: Teams where the testing strategy is tightly coupled with API documentation and design, and organizations that want OpenAPI-driven workflows as their foundation.

Choosing the Right API Testing Tool

There’s no single “best” API testing tool. The right choice depends on your architecture, your team, and where your biggest risk gaps are. For a step-by-step decision framework covering architecture mapping, team assessment, CI/CD fit, maintenance burden, and security considerations, see our companion guide on how to select the best API testing framework.

Here’s how to narrow the field:

Project Requirements

Determine which API protocols you need to test (REST, SOAP, GraphQL, gRPC, async) and which testing types matter most: functional, load, security, or contract. The complexity and scale of your API surface should match the tool’s capacity.

Team Skills and Resources

Some tools require deep coding knowledge (REST Assured, Karate DSL), while others offer no-code or low-code options (Katalon, Postman). Budget matters too. Several tools on this list are free and open source.

Community and Support

A strong community provides troubleshooting resources and keeps you current with best practices. For commercial tools, evaluate documentation quality and support channels before committing.

In many cases, the combination of multiple testing tools produces the most effective API testing process. A common pattern: an open-source library for functional testing where you need maximum flexibility, and a specialized platform for security and performance testing where domain expertise matters more than customization.

Best Practices for Effective API Testing

Here are the practices that matter most when putting API testing tools to work.

Start Early and Automate

Start to test APIs as early in the development lifecycle as possible. Automate functional and regression tests so they run with every build, catching issues before they compound. The tools on this list that offer CI/CD integration (StackHawk, Postman, Bruno, JMeter) make this straightforward.

Layer in Security Testing

Don’t bolt security on at the end. Run security scans automatically in your CI/CD pipelines so vulnerabilities surface alongside other test failures, not in a separate review weeks later.

Use Realistic Test Data

Test data that reflects real-world scenarios and usage patterns surfaces issues that artificial data sets miss. Tools with data-driven testing support (JMeter, Karate DSL, Katalon) make this easier to manage at scale.

Keep Documentation Current

Good API documentation reduces integration problems and support requests. Tools like Swagger generate interactive docs directly from your OpenAPI specs, keeping documentation and implementation in sync.

Challenges in API Testing and How to Overcome Them

Here’s a quick look at the most common obstacles and how the right tooling helps.

Documentation Gaps and Schema Drift

Incomplete documentation stalls testing efforts, and frequent schema changes break existing tests. Tools that generate specs from code (like StackHawk’s API discovery) or documentation from specs (like Swagger, APITect) help close these gaps. Automating schema validation in CI catches drift early.

Test Data and Environment Management

Dynamic or sensitive data requires careful planning, and shared test environments across branches create pollution. Use data-driven testing features (JMeter, Karate DSL) with external data sources, and isolate environments per branch where possible.

Integration Complexity

Ensuring correct data flow across multiple services requires contract testing (Pact, Specmatic) alongside integration tests. Mock servers (SoapUI, Postman, REST Assured) let you isolate your API tests from unstable dependencies.

Achieving Coverage Without Drowning in Maintenance

You’ll never cover everything. Prioritize test cases based on risk rather than trying to test every possible path at once. AI-powered self-healing tests (Katalon) and AI-assisted test generation reduce the maintenance burden as your API surface grows.

Varying Technical Expertise

Teams with diverse skill levels face adoption challenges. Pairing low-code tools (Katalon, Postman) with code-first options (REST Assured, Karate DSL) lets each team member contribute at their comfort level.

The Future of API Testing

The API testing space is moving fast. Here’s what matters most from a tooling perspective.

MCP (Model Context Protocol) is becoming the connective layer between AI coding assistants and the tools on this list. StackHawk’s MCP server lets developers run security scans from within Cursor or Claude Code. Postman’s MCP server connects AI agents to workspaces, collections, and environments. 

In practice, this means developers can describe what they want to test in plain English and the AI handles execution, configuration, and even remediation. Beyond MCP, tools are using AI for test case generation (Katalon, APITect), self-healing test scripts (Katalon), and source code-based API discovery (StackHawk).

The tools that will matter most going forward are the ones that meet developers where they already work: in the IDE, in the CI pipeline, and in the Git repo. MCP, Bruno’s Git-native collections, and StackHawk’s developer-first approach to security testing all point in the same direction.

Conclusion

There’s no shortage of API testing tools in 2026, and picking the right one comes down to your team’s skills, your architecture, and where your biggest gaps are. The tools on this list cover a wide range of needs, from security-first DAST platforms to Git-native API clients to full lifecycle management suites.

The best advice? Don’t overthink the initial choice. Pick a tool that fits your workflow, get it running in CI, and iterate from there. A decent tool that runs on every build beats a perfect tool that only runs when someone remembers to trigger it.

As a top API testing tool, StackHawk offers a modern DAST platform built for developers and AppSec teams from the ground up. Sign up today to test your APIs for the most pressing vulnerabilities, including those in the OWASP API Top 10.