"Testing Kubernetes Network Policies" matching MCP servers:

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

Enables accessibility testing of websites and HTML content using axe-core and IBM Equal Access engines. Supports WCAG compliance checking, multi-viewport testing, and provides detailed violation reports with remediation guidance.

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

Enables connecting to a Kubernetes cluster to manage resources and troubleshoot workloads with kubectl and Helm operations, including logs, scaling, port forwarding, and non-destructive mode.

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 coding agents with visibility into test health through tools for flaky test detection, test quality linting, and LLM evaluation harness, enabling them to triage failures, review test quality, and check prompt changes for regressions.

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.

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

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.

Compare LLM inference costs and find cheap alternatives to OpenAI/Anthropic/DeepSeek. Gonka Network offers an OpenAI-compatible API at up to 6800x lower cost than GPT-4o.

A read-only MCP server for bounded table discovery, deterministic profiling, and maintained-library statistical testing (Welch's t-test and two-proportion z-test) using SQLite, pandas, SciPy, and statsmodels.

Provides AI agents with native access to the Keeta Network Layer 1 blockchain for payments, asset transfers, and compliance-ready financial infrastructure. It features a dynamic, self-describing architecture that allows agents to automatically discover and execute SDK methods at runtime.

Provides AI agents with access to Zero Network documentation, SDK integration guides, and utility tools for crypto-based payments. It enables developers to implement x402 paywalls and per-tool MCP pricing while offering real-time cost estimations and revenue calculations.

A specialized MCP server for QA engineering. It provides tools for user story analysis, test strategy, BDD/Gherkin scenarios, contract testing, integration tests, performance plans, security checklists, and CI/CD pipeline generation, accessible from any MCP-compatible IDE or client.

Enables AI-powered network engineering by providing natural language control over GNS3 network simulations. Supports creating projects, building network topologies, managing devices, controlling simulations, and analyzing network traffic through conversational AI interactions.

Enables managing multiple Kubernetes clusters simultaneously with over 60 tools for cluster operations, resource management, monitoring, RBAC, storage, networking, and more through AI assistants.