"Information on Penetration Testing (Pentest)" matching MCP servers:

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

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.

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

Analyzes Testing Farm jobs, checks job status, and investigates failures with detailed error information.

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.

A multi-language testing automation server that enables AI assistants to discover, plan, and execute tests across six major programming languages. It provides comprehensive tools for repository scanning, automated test execution, and detailed coverage reporting.

Automates Java Maven testing workflows with decision table-based test generation, security vulnerability scanning, JaCoCo coverage analysis, and Git automation.

Orchestrates end-to-end testing of AI-powered incident remediation workflows through declarative YAML scenarios, fault injection, AI response evaluation, and automated command execution with comprehensive reporting.

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.

MCP server for Azure DevOps Server 2022 (on-premises) that enables AI assistants to interact with work items, repositories, builds, and sprints through 29 tools.

MCP server wrapping the full VitoDeploy REST API to manage projects, servers, sites, databases, services, workers, SSL, DNS, and more through any MCP-compatible agent, with 108 tools covering every endpoint.

Record an agent's MCP tool-call workflow once, replay it deterministically for zero tokens, and get a receipt — a snapshot-testing and deterministic-execution layer for Agent Skills.

An MCP server that enables AI assistants to discover and execute Nox sessions for project automation tasks like testing, linting, and building. It provides tools to list available sessions and run them using specific Python versions, tags, or keyword expressions.

Enables AI agents to interact with Appcircle mobile CI/CD platform for build management, signing identities, testing distribution, and reporting.

Deploys and manages projects on Swigs Cloud from any MCP client, turning folders or git repositories into live HTTPS sites in about two minutes.

Enables AI agents to deploy, manage, and configure web applications on sota.io, including project creation, deployment, environment variables, custom domains, and rollbacks.

MCP server that audits npm dependencies against the live registry, providing per-dependency reports on versions behind, deprecation, and license.

Uptime monitoring your AI agent can set up: create HTTP, SSL, ping, TCP and DNS monitors checked from multiple regions, run checks on demand, read and acknowledge incidents, manage cron heartbeats, maintenance windows and status page updates.

Before you move to Python 3.15 (or 3.15t), find every dependency with no wheel for it on your platforms — and the bump that fixes it. CLI, GitHub Action, MCP server.

Enables AI assistants to interact with TrafficMorph for load-testing and CI-failure triage, including run management, profile lifecycle, and domain verification through natural language.

Enables AI assistants to manage website deployments over SFTP/FTPS by listing sites, testing connections, comparing files, previewing changes with approval tokens, creating SHA-256 verified backups, and executing authorized uploads.

Browser acceptance testing for AI agent deliverables: verify agent output in real Chromium from JSON specs, with MCP server, visual regression, multi-browser support and GitHub Actions.

Enables AI coding agents to deploy and manage full multi-service applications on Constructor from a single request, covering image builds, service configuration, start/stop lifecycle, logs, and file syncing on research desks. It handles browser-based sign-in and token renewal automatically so agents can inspect deployments and report results without manual setup.

Enables coding agents to build, test, archive, and run iOS apps on a remote Mac fleet from any environment, with XcodeBuildMCP-compatible tools and live simulator access.

An MCP server that connects Gemini 2.5 Pro to Claude Code, enabling users to generate detailed implementation plans based on their codebase and receive feedback on code changes.

Enables AI clients to deploy static sites, track deployments, and manage sites on a Shiplo account through the Model Context Protocol.

Enables AI assistants to interact with Azure DevOps Server 2022 through natural language, enabling queries and operations on pipelines, pull requests, builds, and repositories.

Enables AI coding agents to orchestrate the full software development lifecycle on GitHub, including planning, issue creation, code review, security triage, and release readiness checks.

An MCP server that enables coding agents to set up and manage webhook infrastructure, including provisioning endpoints, event logs, replay, and testing.

An MCP server that automates the full software development lifecycle through an AI-driven TDD state machine. It handles everything from task decomposition and test-driven development to integration testing and automated pull request creation.