"Information on Security Testing" matching MCP servers:

Provides tools for frontend testing including code analysis, test generation, test execution, and React component testing for Jest and Cypress frameworks.

An MCP Server that enables users to interact with Google's On-Demand Scanning API (v1beta1) through natural language, likely providing capabilities for vulnerability scanning and security analysis of containers and artifacts.

Provides an isolated workspace for testing candidate code, runs tests, and returns deterministic pass/fail verdicts. Enables automated grading of software engineering solutions by ensuring reproducible test runs.

AI-optimized Vitest interface that provides structured test output, visual debugging context, and intelligent coverage analysis for more effective AI assistance with testing.

Chain of Draft Server is a powerful AI-driven tool that helps developers make better decisions through systematic, iterative refinement of thoughts and designs. It integrates seamlessly with popular AI agents and provides a structured approach to reasoning, API design, architecture decisions, code r

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

Enables compiling Lean 4 proof snippets on the local machine against a Mathlib project and returns structured compiler feedback — status, one-line hints, and the compiler's real error, warning, and information messages — so a model can iterate on proofs instead of guessing. Compilation is serialized, timeouts kill stuck tactics, and rejected code is reported as a normal result rather than a tool failure.

Provides LLMs with deterministic math tools for sandboxed expression evaluation, descriptive statistics, primality testing, prime factorization, GCD/LCM, quadratic solving, and base conversion. Every operation runs real code rather than relying on the model's arithmetic, with expression parsing restricted to a whitelist of operators, constants, and functions.

Enables AI models to dynamically create and execute their own custom tools through a meta-function architecture, supporting JavaScript, Python, and Shell runtimes with sandboxed security and human approval flows.

Enables R package development, testing, jamovi module building, and arbitrary R code execution from MCP clients like VSCode, using an RStudio Desktop integration.

An MCP server that bridges AI to Roblox Studio, enabling execution of Luau scripts, instance manipulation, play-testing control, and Open Cloud operations via natural language.

An MCP server that enhances sequential thinking with meta-cognitive capabilities including confidence tracking, hypothesis testing, and organized memory storage through graph-based libraries and structured JSON documents.

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.

A comprehensive learning project demonstrating MCP server implementation with tools for calculator operations, file management, and system information retrieval, including Google ADK integration patterns and best practices.

A minimal reference implementation of an MCP server that responds with "Hello, World" via Streamable HTTP. Serves as a baseline for integration testing and MCP client development with production-ready features including health checks, metrics, and containerized deployment.

Provides a universal bridge to interact with any OpenAI-compatible LLM API (local or cloud), enabling model testing, benchmarking, quality evaluation, and chat operations with performance metrics.

Provides a universal developer operations and diagnostics toolkit with sandboxed code execution, algorithm stress testing, security secret scanning, AST-based code fixes, and a visual dashboard for ERD, port/process inspection, and differential testing.

A Model Context Protocol server framework featuring dynamic tool loading and automatic tool discovery from a dedicated directory. It leverages FastMCP to provide a robust environment for building, configuring, and testing individual Python-based tools.

A local Ethereum contract analysis tool that retrieves on-chain information, integrates Etherscan and RPC data, and automatically executes view functions to provide comprehensive contract insights.

Enables pre-execution security checks and sandboxed execution for AI agent workflows, including prompt-injection detection, MCP rugpull and sampling abuse protection, untrusted tool-output sanitization, loop circuit breaking, SQL AST validation, PII redaction, and ephemeral Python execution.

An MCP server that enhances AI agents' coding capabilities by providing zero hallucinations, improved code quality, security-first approach, high test coverage, and efficient context management.

An MCP server that automatically optimizes AI prompts using evolutionary algorithms, helping improve prompt performance, creativity, and reliability through iterative testing and refinement.

A Model Context Protocol server built with FastMCP that enables dynamic tool loading and configuration from individual Python files. It provides a flexible framework for automatically discovering, testing, and running tools via Stdio or HTTP transport modes.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools for calculations and greetings, plus system information resources.

A simple MCP server that provides a tool to fetch current weather information for cities using the Open-Meteo API, communicating through stdin/stdout.

A Model Context Protocol server that retrieves current weather information for any city using the OpenWeatherMap API, designed for integration with Claude Code.

A secure terminal execution server that enables controlled command execution with security features and resource limits via the Model Context Protocol (MCP).

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.

A boilerplate project for quickly developing Model Context Protocol (MCP) servers using TypeScript SDK. Includes example tools like calculator and greeting functions, plus system information resources.

Provides comprehensive documentation about AWS AgentCore framework to GenAI tools, enabling users to build production-ready AI agents with enterprise-grade security, observability, and scalability. Offers guidance on identity management, API integration, monitoring, code execution, memory storage, and tool integration for AI agents.