Discover our curated collection of MCP servers for security & testing. Browse 2747 servers and find the perfect MCPs for your needs.
Enables secure execution of system commands via the MCP protocol using an allowlist.
Automates Playwright tests using the Model Context Protocol.
Implements a server designed to pause before responding to requests, useful for testing.
Enables LLM agents to safely execute arbitrary Python code in a secure, throw-away sandbox.
Provides a secure boilerplate for exposing AI-compatible APIs to various large language models and agents using the Model Context Protocol.
Provides remote network access to HexStrike AI's extensive suite of 150+ security tools for AI agents without requiring local client files.
Serves as a config-driven, modular Model Context Protocol server enabling the execution of various plugins and tools.
Provides enterprise-grade debugging capabilities for Node.js and TypeScript applications, designed for interactive use by AI agents.
Isolate processes with OS-native filesystem and network controls, offering a lightweight security solution without containers or virtual machines.
Empowers AI coding assistants with visual perception for precise frontend debugging and verification.
Provides a secure, isolated environment for executing Python code in ephemeral Docker containers with automatic dependency management and file persistence.
Exposes mobile automation capabilities using Appium as Model Context Protocol (MCP) tools for Large Language Model (LLM) agents.
Provides command-line, TUI, and MCP server interfaces to the MITRE EMB3D knowledge base for embedded security information.
Detects visual layout bugs using deterministic DOM analysis, identifying issues like overflow, spacing, typography, and responsive regressions.
Provides secure and standardized file and command operations for Windows Subsystem for Linux (WSL) environments, resolving UNC path issues for integrated development environments.
Automates web interactions with Playwright, offering robust security features and a query-first design optimized for intelligent agents.
Validates MCP tool definitions, scores AI agent system prompts for governance, and estimates costs across major models.
Enables AI agents to interact with terminal applications by converting raw terminal output into a structured Terminal State Tree.
Enforce rigorous development practices and enhance efficiency for AI coding tools like Claude Code and Codex CLI through a comprehensive governance harness.
Routes shell commands through a token-optimizing engine to drastically reduce LLM context window usage for any MCP-compatible client.
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