"Methods to Test API Endpoints" matching MCP servers:

Enables AI agents to call real API endpoints and verify responses against OpenAPI specs, supporting contract testing, auth presets, spec diffing, and health checks.

Enables AI agents to drive API testing from YAML definitions, executing and chaining requests without hand-written curl, while keeping credentials out of the conversation and responses token-cheap, plus a VANDER-based QA review of endpoints.

Enables testing and interacting with REST API endpoints through MCP clients such as Claude and Cline, supporting multiple HTTP methods, authentication, custom headers, and configurable response limits.

Enables testing and interacting with any REST API endpoints directly from development environments through MCP clients, including support for multiple HTTP methods, authentication methods, custom headers, SSL verification control, and response size limiting.

Enables testing and interaction with REST API endpoints from MCP clients such as Claude and Cline, supporting multiple HTTP methods, authentication, custom headers, SSL verification control, and response-size limiting.

Enables users to test and interact with any REST API endpoints directly from their development environment through MCP clients such as Claude and Cline. Supports GET, POST, PUT, DELETE, and PATCH requests with configurable authentication, custom headers, SSL verification, and response size limits.

Enables testing and interacting with REST API endpoints through MCP clients such as Claude and Cline, with support for common HTTP methods, authentication, custom headers, SSL verification settings, and response size limits.

Enables testing and interacting with REST API endpoints through MCP clients like Claude and Cline, supporting multiple HTTP methods, authentication, custom headers, and response size limits.

Enables users to test, debug, and interact with REST API endpoints directly from MCP clients such as Claude and Cline. Supports multiple HTTP methods, authentication, custom headers, SSL verification controls, and configurable response size limits.

An automated testing MCP server that converts test cases into a fixed JSON format, runs them case-by-case, and provides a visual report with review support for cases that cannot be automatically judged.

An MCP server that gives AI coding agents the ability to analyze a Python repository's test health: coverage, flaky tests, and ML-based pull-request risk prediction.

An intelligent MCP toolset for software testers that monitors code changes, analyzes test impact, recommends tests, and assesses risk, supporting multiple AI coding frameworks via dual transport modes.

Enables management of TestMu AI test projects, test cases, test runs, and integration with Jira, HyperExecute, and AI insights through natural language.

Test coverage intelligence MCP server for TypeScript and JavaScript projects. Analyzes coverage reports to find untested functions, computes cyclomatic complexity, and suggests test cases locally.

This server assists with A/B testing by calculating required sample sizes and necessary test durations. It provides a suite of significance tests, including z-test, chi-square, and Fisher exact methods, while evaluating the risks of premature peeking.

Gives AI assistants structured access to a test automation stack so they can run suites, inspect failure details and captured output, look up test data, and file Jira bugs (or drafts) only for confirmed defects. It works with any framework that emits JUnit XML, letting assistants triage flaky, environment, and test-data issues alongside real product defects.

Auto-generates and manages test cases for any project from feature descriptions, with tools for adding, listing, updating, and exporting test cases via Claude.

MCP server that generates ISO/IEC/IEEE 29119-3 compliant test plan drafts from project information, providing a structured resource for the standard's test plan outline and a tool for draft creation.

A specialized testing harness that enables AI assistants to thoroughly test other MCP servers by connecting to them, discovering their tools/resources/prompts, executing test calls, and performing end-to-end validation with LLM integration.

Contract-driven test enforcement and reporting for LLM-generated code via MCP, VS Code, Copilot CLI, Claude, Cursor, or Python SDK.

Enables migration of test automation projects from WebDriverIO to Playwright using AST-based transformations. Provides tools for analyzing tests, converting syntax, refactoring to Page Object Model, and generating migration reports.

MCP server for self-hosted qTest Manager, enabling natural-language management of projects, modules, test cases, requirements, traceability, and test execution via the qTest REST API.

Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.

Enables Claude Code to analyze flaky tests, find failure patterns, suggest fixes, and query test history, failure patterns, and correlated failures from Test Ledger.

ocal-first, read-only MCP server that audits repository test architecture across ten language ecosystems. It returns deterministic evidence-backed findings, blockers, rankings, and repository-native test plans without modifying source files.

MCP server for managing Apidog test cases, scenarios, suites, and test data, providing full read/write access to Apidog's test management features.

Enables AI agents to manage Autotest AI projects, screens, test cases, and test runs through natural language commands.

Generates structured, comprehensive test cases from user stories, API specs, or raw text, with automatic Excel export and Playwright automation code generation.

MCP server voor het maken van testcases. Maar ook voor het inzetten van test technieken en heuristieken.

Enables test execution and management through MCP clients, allowing retrieval of projects, listing tests, executing tests with browser selection, and monitoring results.