"Villager 0.2.1rc1 Framework MCP Auto Penetration Testing" 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.

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.

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

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.

It enables AI coding agents to persist local scripts as callable MCP tools with JSON Schemas, execute them via subprocess, and expose new tools immediately without restarting. This reduces token and latency costs for repetitive multi-step file, data, and batch operations.

Enables natural-language materials simulation workflows in which agents write native scientific scripts, persist research projects, execute and monitor jobs on Slurm, recover failed tasks, and analyze or hand off results.

A general-purpose MCP server that provides utility tools for echo, date/time, and file operations within Claude Code and Claude Desktop. It functions as an extensible framework designed to help developers easily build and register custom Python-based tools.

A comprehensive framework for building reliable Python MCP servers that enforces incremental development practices through Cursor Rules, featuring built-in security measures and a smart rule system.

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.

Universal Python code execution MCP server that lets LLMs write and run Python for any task, with auto-install packages, streaming output, and automatic file display.

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

Stdio MCP Server wrapping custom Python runtime (LocalPythonExecutor) from Hugging Faces' smolagents framework. The runtime combines the ease of setup (compared to docker, VM, cloud runtimes) while providing safeguards and limiting operations/imports that are allowed inside the runtime.

A lightweight framework for building and running Model Context Protocol (MCP) servers using FastMCP, providing tools for development, debugging, and server management.

This MCP server is the official resource of the Flowbite UI framework and enhances development of websites, layouts, and themes using Tailwind CSS

Auto-discovers running marimo notebooks and exposes tools for reading, editing, and running cells via MCP, supporting both HTTP and VS Code backends.

Provides tools for interacting with Jupyter notebooks, allowing users to read, add, and execute notebook cells. It supports full notebook execution and metadata retrieval through the FastMCP framework.

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.

An MCP server framework featuring dynamic tool loading and a modular one-tool-per-file architecture for rapid development. It supports both Stdio and HTTP transport modes, offering automated test generation and centralized configuration management.

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.

MCP server that enables Claude Code to delegate code generation and debugging to OpenAI Codex, with stall detection and auto-recovery.

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 minimal TypeScript starter template for building Model Context Protocol (MCP) servers with auto-loading architecture for tools, resources, and prompts. Includes code generators, dual transport support (stdio/HTTP), and production-ready structure.

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.

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.