"Website penetration testing and security vulnerability assessment tools" 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.

Provides a remote coding environment for AI to publish static websites as live URLs, with live code editing and sandbox execution.

An MCP server that provides a persistent sandbox for AI coding agents to explore codebases server-side, returning only compact summaries to reduce context consumption.

Enables AI assistants to perform controlled Linux system administration tasks like reading logs, managing services, cron jobs, WordPress, and executing sandboxed Python code, with strict security constraints.

Audits npm package dependencies for security vulnerabilities, providing detailed reports and fix recommendations with MCP integration.

Enables Claude Agent SDK agents to safely operate a remote user machine via a WebSocket tunnel, providing six client__* MCP tools with path fencing and phase-switch adjudication.

Enables coding agents to perform file, search, patch, git, process, test, package, network, and system operations through 60 typed MCP tools with structured inputs/outputs, structured errors, and a full event journal, replacing terminal use with a typed machine API.

A Model Context Protocol (MCP) server that provides TypeScript development tools for automated refactoring and code analysis.

Extends VS Code Copilot with MCP tools for persistent semantic memory, code indexing and RAG search, sandboxed Python/shell execution, web fetch/search, dynamic tool management via a web UI, and structured multi-step reasoning.

A collection of production-ready MCP tools for common tasks such as web search, code execution, file operations, and database queries, enabling AI agents to perform these actions through a unified interface.

MCP server wrapping DeepSeek's agent harness tools into minimal/standard modes, enabling persistent shell, file editing, search, job management, and more via natural language.

Guides problem-solving by breaking down complex problems into steps and recommending appropriate MCP tools for each stage, with confidence scores and rationales for tool suggestions.

Enables dynamic creation and execution of custom tools/functions in multiple programming languages at runtime, exposing them to MCP clients like Claude.

A meta-MCP server that orchestrates tools from multiple MCP servers, enabling complex Python workflows with loops and conditionals.

A Model Context Protocol server for time manipulation tasks, enabling AI models to get the current date/time and calculate duration between timestamps.

A comprehensive Model Context Protocol server providing access to 70+ IT tools for developers and system administrators, including encoding/decoding, text manipulation, hashing, and network utilities.

A dynamic MCP server that automatically discovers Python files in a directory and exposes them as tools to any MCP-compatible AI client, allowing users to easily create and deploy custom AI tools.

A Model Context Protocol server providing AI assistants with comprehensive project, task, and subtask management capabilities with project-specific storage.

Gives any MCP-compatible AI chat or agent a safe, model-neutral coding runtime with file read/search, structured multi-file patches, command execution, interactive sessions, and git operations, all confined to a single workspace and gated by permission modes.

Provides access to OpenAI's advanced models (including o3) with integrated web search, Python code interpreter, and combined analysis capabilities. Enables users to perform web searches, execute code in sandboxed environments, and combine search with analysis through natural language.

Gives MCP-compatible AI clients safe, hands-on access to local codebases: file reading/search, multi-file patches, command execution, interactive sessions, Git inspection, and coordination of local agent providers such as Antigravity and OpenCode.

Empower any MCP-compatible AI Agent(MCP Client) with engineering-grade capabilities to understand, modify, run, and deliver real-world code repositories.

Provides AI agents with tools to retrieve live system statistics (CPU, memory) and safely evaluate basic arithmetic expressions.

Enables AI agents to execute tools securely with Docker isolation, tier-based permissions, and feature flags, providing a centralized tool registry and MCP server.

A comprehensive MCP server providing tools for AI agents to interact with code, including reading symbols, importing modules, replacing text, and sending OS notifications.

Enables AI agents to code and debug Commodore PET software using the VICE emulator, with CLI and MCP tools for session control, screen reading, memory manipulation, and testing.

Enables any MCP client to read, search, patch, and execute commands in a codebase, including interactive sessions and git operations, with permission modes and safety boundaries.