"Testing Kubernetes Network Policies" matching MCP servers:

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

Provides tools for frontend testing including code analysis, test generation, test execution, and React component testing for Jest and Cypress frameworks.

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.

An MCP server that executes tox commands to run Python tests within a project using pytest, allowing users to run all tests or specific test groups, files, cases, or directories.

An MCP server that enables interaction with Kubernetes resources through natural language interfaces like Goose CLI, allowing users to get, read, and patch Kubernetes resources.

Provides a set of read-only Kubernetes functions via an MCP server, enabling interaction with Kubernetes clusters through agents or coding assistants like GitHub Copilot.

An MCP server that provides seamless integration with the Neo N3 blockchain, allowing Claude to interact with blockchain data, manage wallets, transfer assets, and invoke smart contracts.

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.

A Python code execution sandbox based on IPython and Docker. Stateful code execution, file transfer between host and container, configurable network access.

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

Read-only MCP server for safe Kubernetes inspection, diagnosis, and debugging. Supports Kubernetes core, Helm, Argo Workflows, and Argo CD.

Enables AI coding agents to run Kubernetes inspection and Terraform plan/apply operations inside ephemeral gVisor-sandboxed jobs with short-lived, narrowly-scoped credentials, while routing destructive changes through a human approval gate.

Allows executing shell commands within a secure Docker container through Claude's MCP interface, providing Kubernetes tools and isolated environment without host Docker daemon access.

Creates short-lived, offline JavaScript sandbox containers for safe code execution via MCP, with no network access and strict resource limits.

Multi-Agent Mesh Network MCP server that spawns specialized AI agents working in parallel to solve complex coding problems, providing 3.64x faster performance through distributed intelligence.

An MCP server that enhances sequential thinking with meta-cognitive capabilities including confidence tracking, hypothesis testing, and organized memory storage through graph-based libraries and structured JSON documents.

Enables R package development, testing, jamovi module building, and arbitrary R code execution from MCP clients like VSCode, using an RStudio Desktop integration.

A minimal reference implementation of an MCP server that responds with "Hello, World" via Streamable HTTP. Serves as a baseline for integration testing and MCP client development with production-ready features including health checks, metrics, and containerized deployment.

Provides a universal developer operations and diagnostics toolkit with sandboxed code execution, algorithm stress testing, security secret scanning, AST-based code fixes, and a visual dashboard for ERD, port/process inspection, and differential testing.

Provides a universal bridge to interact with any OpenAI-compatible LLM API (local or cloud), enabling model testing, benchmarking, quality evaluation, and chat operations with performance metrics.