"Testing Library" matching MCP servers:

Python library for agent-operable experiment evidence and control. Bring any training code

A CLI tool that integrates with Claude Desktop to allow users to retrieve their Goodreads library data through MCP.

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

A production-ready template for creating Model Context Protocol servers with TypeScript, providing tools for efficient testing, development, and deployment.

AI-Powered Red Team MCP Server enabling autonomous penetration testing via Model Context Protocol with 44+ security tools for AI agents.

Enables MCP-capable agents to author, compile, run, and commit generative music E-- Recipes from a library catalog, completing the full authoring loop.

AI-driven penetration testing MCP server that equips Claude with 13 tools for automated reconnaissance, analysis, vulnerability validation, and exploitation.

A production-ready Python library for building MCP servers with agent orchestration and domain-specific presets for platforms like GitHub, Slack, and Notion.

Manages MCP servers within the DSH Web GUI, enabling server CRUD, enable/disable, testing, per-session connection selection, scoped tool registration, and OAuth browser authorization.

Allows MCP clients like Claude Desktop or Cursor to perform Unity Editor actions, including asset management, scene modification, and game mechanic testing.

Enables secure integration with Metasploit Framework for AI assistants, providing comprehensive access to penetration testing tools, module management, payload generation, and database operations. Designed for authorized security testing and defensive analysis with 28 specialized tools covering complete MSF functionality.

Enables LLM hosts like Claude Code, Cursor, or Claude Desktop to drive YeepForge's 28 web penetration testing tools (recon, crawling, SQLi/XSS testing, nuclei scans) and set engagement targets via Model Context Protocol, using the host's own LLM subscription.

AI-native security testing platform with native MCP support, enabling automated penetration testing, vulnerability discovery, and attack-chain analysis through conversational commands.

🧱 easy fast local-first microVM runtime and library

Persona-driven LLM agent testing for macOS and web apps through a local MCP daemon, enabling autonomous GUI testing with human-like behavior.

Enables managing persistent AI workers through MCP tools for versioning, safe testing, deployment, approvals, and run lifecycle with tenant isolation and policy enforcement.

MCP server that connects an LLM via Ollama to security tools for autonomous or guided penetration testing from a terminal interface.

A Python framework that enables secure hardware control through the Model Context Protocol, allowing AI agents and automation systems to interact with physical devices across multiple platforms.

AI-powered penetration testing framework that can operate as an MCP server, enabling automated security assessments through natural language commands.

Provides multilingual text translation capabilities using Baidu Translate API with support for language detection and advanced features like context filling and zero-width character obfuscation for testing agent robustness.