"How to Test Kubernetes Network Policies" matching MCP servers:

Provides access to Kubernetes troubleshooting runbooks, enabling search, discovery, and retrieval of guides for common issues like pod crashes, node problems, and network failures.

Manages Kubernetes clusters through kubectl and Helm operations including pod cleanup, node management, and troubleshooting.

TypeScript implementation of Kubernetes cluster operations for pods, deployments, services.

Enables AI assistants to understand lab topologies, follow operational principles, and interact with real network devices through observable terminals while keeping private access information hidden.

Local-first MCP server that lets AI agents design Cisco-style networks and generate L1/L2/L3 topology diagrams, device tables, and AI-ready context files.

Provides read-only access to UniFi Network consoles for sites, devices, clients, vouchers, networks, Wi-Fi, and firewall configuration, with optional opt-in tools for controlled write operations and legacy controller support.

Enables users to get the current temperature for a city through a single MCP tool, using Open-Meteo data with no API key required.

A Model Context Protocol server providing network diagnostic tools for AI agents, including connectivity testing, batch operations, local network info, and pcap analysis.

Provides MCP tools for governed multi-vendor network device operations, including configuration management (backup, diff, merge, replace, rollback) and read-only queries (facts, interfaces, BGP, LLDP, ARP) via NAPALM, with optional NetBox source-of-truth integration.

Enables safe, read-only interaction with Kubernetes clusters, allowing users to list resources and fetch logs without any create/update/delete operations.

Enables diagnosing Kubernetes clusters without creating or changing cluster objects, with tools to inspect health, workloads, events, storage, RBAC, custom resources, logs, and configuration.

A minimal MCP server template for testing and development, providing example implementations with fastmcp and Python.

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.

A basic MCP server built with the FastMCP framework that provides fundamental mathematical operations like addition, subtraction, multiplication, and division. It serves as a demonstration for integrating math-based tools into MCP-compatible environments like Cursor IDE.

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.

Enables AI assistants to unleash a crowd of role-played virtual users — impatient shoppers, seniors, keyboard-only users, privacy hawks, chaos monkeys — on a website. Each persona browses in a real Chromium browser, files UX/QA findings in character, and the site receives a damage report with an S–F survival grade. Accusations can be cross-examined by up to three independent verification engines

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

mcp-server-test

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

Enables searching and retrieving documentation from crawled documentation sites as an MCP server, allowing coding agents to query real docs instead of relying on training data.