"Methods to Test API Endpoints" matching MCP servers:

Enables Claude to generate executable test cases from decision tables in CSV, JSON, or Markdown formats. Provides intelligent test planning guidance and generates Playwright/API test code with TypeScript support.

MCP server for deterministic local test execution and normalized test result reporting, supporting pytest and Jest with coverage summaries.

A full-stack API automation testing server that parses OpenAPI/Swagger/Postman/HAR specs, generates comprehensive test scenarios and executable code, and provides AI-powered review and auto-fix.

A server implementation of the Model Context Protocol (MCP) that provides REST API endpoints for managing and interacting with MCP resources.

An MCP Server that enables natural language interaction with the Open Policy Agent REST API, allowing users to manage policies, decisions, and data through conversational interfaces.

MCP server that gives AI agents isolated, named Linux computers with stable IDs and lifecycle control. Supports multiple backends like Docker, Fly Machines, Modal, and E2B, with a dashboard for managing sandboxes.

Enables AI coding agents to safely run commands, install dependencies, test, and modify code inside disposable, policy-enforced Docker sandboxes isolated from the host, returning results and diffs.

Enables an LLM or agent to drive a VUnit HDL unit-testing project end to end: list tests, compile, run, and inspect reports and per-test logs.

Provides an isolated workspace for testing candidate code, runs tests, and returns deterministic pass/fail verdicts. Enables automated grading of software engineering solutions by ensuring reproducible test runs.

Enables AI assistants to write and execute C# code directly inside Autodesk Civil 3D, providing full API access through code generation and execution.

A secure, containerized workspace for LLMs to autonomously code, test, and debug projects without risking the host machine.

MCP bridge between an AI assistant and the Godot editor, enabling control via 6 tools (call methods, run GDScript, screenshots, etc.) over WebSocket.

AI-optimized Vitest interface that provides structured test output, visual debugging context, and intelligent coverage analysis for more effective AI assistance with testing.

Enables AI agents to perform federated data transfers and remote code execution on HPC endpoints via Globus, wrapping the Globus CLI and Globus Compute SDK.

Enables AI agents to run Jest/TypeScript tests in isolated workspaces for Test-Driven Development workflows.

Enables Gemini-powered multimodal analysis (video, audio, image, documents), Google search, and code execution via the API易 service. Supports Docker deployment and flexible configuration.

MCP server that gives AI coding agents full control over Cypress test execution, allowing them to run, debug, and iterate on E2E tests directly from MCP-compatible agents.

Enables AI assistants to write and debug integration tests by providing live access to DOM structure and executing code directly in test environments.

Language-owned MCP gateway and execution-host coordination for Hara, exposing read-only tools for runtime introspection, evaluation, calls, and checks, with an optional deterministic test fixture for development.

Provides structured, sandboxed test and lint feedback for coding agents, returning compact typed verdicts with failure fingerprints instead of raw runner output. It enables impact-selected test execution in isolated containers, distinguishing pre-existing failures from regressions.