"Villager 0.2.1rc1 Framework MCP Auto Penetration Testing" matching MCP servers:

Provides access to over 40 industry-standard penetration testing tools, including Nmap, SQLMap, and Metasploit, within an isolated Kali Linux Docker container. It enables security professionals to perform comprehensive network reconnaissance, web application testing, and vulnerability research through natural language commands.

Enables Claude to search and install skills from a database of ~200k scraped Claude skills, MCP servers, and plugins.

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

Human-in-the-loop automation framework. Log them in, watch them run.

MCP server for testing GitHub Actions workflows locally using nektos/act.

Code-aware browser testing agent — reads your codebase, understands functionality, tests every element, reports with screenshots. Works as MCP server for Cursor/Claude Code or standalone CLI.

A powerful Model Context Protocol framework that extends Cursor IDE with tools for web content retrieval, PDF processing, and Word document parsing.

Enables submitting FMF-based test requests to Testing Farm and listing available OS composes for testing.

Drives Android, iOS, smart TV (Android TV, Tizen, webOS), web and Bluetooth (BLE) devices from an agent: start a session, tap, type, swipe and assert by XPath, visible text, OCR or image, then save the steps as a replayable CSV test suite.

Provides usage data from @ccusage/pi and tools to switch between AI providers (e.g., Claude Code, OpenAI Codex, CursorAI) using load-balancing or high-availability strategies.

Exposes an installed LCU runtime to MCP clients as computer-use tools, maintaining persistent sessions across related calls and handling recognized native-app consent locally for clients without approval dialogs.

A comprehensive MCP server for Linux automation operations management, providing 88 tools across 8 categories for file, system, process, network, compression, and package management via SSH connections.

Enables AI agents to crawl live DOMs into compact accessibility maps, generate frontend and backend test plans, execute self-healing Playwright QA locally without token replay, and compile passing flows into native .spec.ts files.

A middleware system that connects large language models (LLMs) with various tool services through an OpenAI-compatible API, enabling enhanced AI assistant capabilities with features like file operations, web browsing, and database management.

Lets a running interactive agent session receive outside events — webhooks, cron timers, files landing in a directory — pushed directly into its transcript as they happen. Users can drop a small source plugin file into their project and have the agent notice and act on external triggers mid-session, with no human re-prompting and no restarts.

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 TypeScript framework for building Model Context Protocol (MCP) servers with automatic discovery and loading of tools, resources, and prompts.

An LLM-driven API testing platform exposed over MCP, enabling declarative test definition and DAG-based execution.

Enables automated testing and coverage reporting for MCP services with test execution, file generation, and mock service creation. Provides comprehensive testing infrastructure including Jest integration, coverage reports, and health checks for the MCP ecosystem.

MCP server that enables AI agents to programmatically run tests, query results, and receive intelligent recommendations about test execution strategy.

Gives AI assistants a read-only, offline interface to the FinOps Foundation's published guidance — its principles, phases, domains, 22 capabilities with Crawl/Walk/Run maturity assessments, personas, and an 88-entry KPI library — so FinOps questions are answered with the Foundation's own text and formulas rather than improvised ones. It exposes 11 tools, document resources, and four guided prompts over stdio, with every response carrying its source URL and license.

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.

A communication framework that enables multiple AI agents to collaborate through asynchronous messaging, agent registration, and discovery. It facilitates complex task coordination and real-time discussion across distributed agent workflows using the Model Context Protocol.

Enables automated packaging of Maven backend and npm frontend projects, with SVN version retrieval and both step-by-step and one-click build workflows.

Enables Claude Code to read and write issues on the Testing Platform via natural language, including listing projects, filtering issues, creating and updating issues, and adding comments.

Automates internal system form submissions by reading data from Excel/CSV or Google Sheets and using Playwright to navigate menus and fill form fields, with support for both visible and headless modes.

Provides testing and quality assurance tools for AI agents via MCP, enabling generation of test cases, mock data, API mocks, coverage analysis, and assertions.

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.

A server that automates screenshot capture and document processing, allowing users to convert screenshots into PDFs and extract text through natural language commands.

A lightweight, local-first MCP server for executing HTTP requests and managing API collections and environments without cloud dependencies. It enables testing APIs, handling authentication, and importing OpenAPI specifications directly within MCP-compatible workflows.