The Xcode MCP Server is a server based on the Model Context Protocol, providing comprehensive Xcode integration capabilities for AI assistants, including project management, file operations, build testing, CocoaPods and Swift package management, and iOS simulator tools.

MCP Appium is an intelligent mobile automation server based on the model context protocol, providing cross - platform mobile app testing tools for AI assistants, supporting iOS and Android platforms, and featuring intelligent element location, session management, and automated test generation functions.

mcp-chat is an open-source and general-purpose MCP client tool for testing and evaluating MCP servers and proxies. It supports command-line interaction and web mode, can connect to various MCP servers (JS/Python/Docker), and provides functions such as chat history recording, model selection, and system prompt customization to help developers debug MCP services.

xk6-mcp is a k6 extension for testing Model Context Protocol (MCP) servers, supporting interaction with MCP servers via stdio or SSE transmissions.

This project is a proof-of-concept (POC) that demonstrates how to implement the Model Context Protocol (MCP) through a custom host for testing agentic systems. Core features include OpenAI-compatible API, Google Gemini integration, streaming response support, and tool invocation capabilities.

An OAuth2 authorization server project based on Spring Boot 3 and Java 24, supporting GraalVM native images, CRaC checkpoint restoration, local AI model testing, and Docker deployment.

AutoSpectra is an all-in-one AI agent automation platform that provides an integrated solution for browser automation, API testing, debugging tools, etc., and is compatible with multiple AI model systems.

An implementation of a k6 load testing server based on the Model Context Protocol

This project is an MCP server for the Metasploit framework, providing a bridge between large - language models (such as Claude) and the Metasploit penetration testing platform, and supporting the control of complex security testing workflows through a natural language interface.

The Zebbern Kali MCP server is a comprehensive penetration testing platform based on the Model Context Protocol (MCP), providing 139 functions for AI assistants (such as GitHub Copilot) to directly execute security tools on the Kali Linux system through a standardized API, covering network reconnaissance, web application testing, password cracking, vulnerability exploitation, and Active Directory attacks.

Unity-MCP is an open - source project that connects the Unity game engine with AI assistants. It implements AI - assisted development, automated testing, and runtime debugging functions through the Model Context Protocol.

MCPStudio is an AI tool integration platform similar to Postman, providing a visual interface for creating, testing, and managing Model Context Protocol servers, simplifying the connection process between AI systems and external services.

An implementation of a k6 load testing server based on the Model Context Protocol framework, supporting custom test durations and the number of virtual users, providing simple APIs and real-time test outputs.

A documentation management system based on the Model Context Protocol (MCP), providing functions such as resource templates, documentation processing, task management, and integration testing.

A minimalist Model Context Protocol (MCP) server based on AWS Lambda and API Gateway, deployed using the Serverless Framework, supporting local development and testing.

ZAP-MCP is a bridging protocol between OWASP ZAP and AI models, which realizes AI-driven automated security testing and analysis functions through a standardized interface.

A minimal server/client application implementation based on the Model Context Protocol (MCP) and Azure OpenAI, including the FastMCP server, Playwright testing framework, and MCP-LLM Bridge conversion function.

MCPwner is a security research automation server based on the Model Context Protocol, integrating multiple security testing tools (SAST, SCA, secret scanning, etc.) to provide a unified interface for LLM - driven security analysis workflows.

PentestThinkingMCP is an automated penetration testing framework based on large language models and the MCP protocol. It can plan attack paths through Beam Search and MCTS algorithms, providing step reasoning, tool recommendation, and key path analysis for CTF, HTB, and real - world penetration testing.

The Sauce Labs MCP Server is a model context protocol server fully integrated with the Sauce Labs testing platform, supporting AI assistants to manage the device cloud, test tasks, build analysis, and monitor the test infrastructure through natural language interaction.

The MCP Server Testing Tool is a configuration-driven testing solution for verifying, benchmarking, and ensuring the reliability of MCP servers integrated with AI models. It supports automatic tool discovery, generation of intelligent test cases, execution of validation, and generation of detailed reports.

FFUF MCP is a bridge that connects the high-speed web fuzzing tool FFUF with the Model Context Protocol (MCP) ecosystem. It integrates FFUF features into MCP-compatible applications through a standardized protocol, supporting automated security testing and AI-assisted workflows.

The plugged.in App is a comprehensive web application for managing Model Context Protocol (MCP) servers, providing a unified interface to discover, configure, and use AI tools across multiple MCP servers. It supports multi - workspaces, an interactive testing platform, tool management, resource discovery, etc., can be integrated with various MCP clients, and supports self - hosted deployment.

The MCP test client is a tool for testing Model Context Protocol servers, providing simple interfaces for tool calls and response validation.

A powerful test automation framework based on Playwright and TypeScript, adopting the page object model design pattern, supporting data-driven testing, and integrating the MCP service to enhance test recording and playback functions.

Hoverfly MCP Server is a Model Context Protocol (MCP) server based on Spring Boot that integrates the Hoverfly simulation tool into the AI assistant ecosystem, supporting dynamic simulation of third - party APIs to solve the problem of external service dependencies in development and testing.

MCP Cases is a multi - functional format based on the Model Context Protocol, used for automation testing, server simulation, protocol validation, and documentation generation.

A service implementing the Model Context Protocol (MCP) for managing Claude's memory and knowledge graph, supporting local development and testing.

The MCP Internet Speed Test is an experimental project that provides network performance testing tools for AI models through the standardized MCP protocol, including functions such as download/upload speed, latency, and jitter measurement.

A server that provides a Model Context Protocol (MCP) interface for the AFL++ fuzz testing framework, allowing the creation and management of fuzz testing workspaces, building of instrumented targets, importing of corpora, starting/stopping of fuzz testing tasks, and analysis of test results through a standardized API.

This is a curated list of resources for the Model Context Protocol (MCP) ecosystem, covering multiple categories such as official resources, development tools, MCP servers, web integrations, databases, blockchains, AI integrations, voice, mobile applications, development environments, security testing, productivity tools, and system tools.

The LocalStack MCP server is a model context protocol service that provides tools to manage LocalStack containers and related tasks, simplifying local cloud development and testing. It supports container operations, infrastructure deployment, log analysis, IAM policy management, chaos testing, and state snapshots, etc.

A Model Context Protocol server for DICOM connection testing

An MCP server that exposes the PyTorch Lightning framework to tools, agents, and orchestration systems through structured APIs, supporting functions such as training, inspection, validation, testing, prediction, and model checkpoint management.

This project is an MCP server designed for the Metasploit Framework, providing an integrated interface between large language models and the penetration testing platform, and supporting the control of complex security testing processes through natural language.

This is a Node.js server based on the Model Context Protocol (MCP). It encapsulates the Appium mobile automation capabilities into MCP tools, enabling LLM intelligent agents to control Android or iOS applications through natural language instructions, achieving automated testing and interaction.

An implementation of a k6 load testing server based on the Model Context Protocol

This is a project demonstrating how to create and test an MCP (Model Context Protocol) server, including environment setup, server creation, addition of tools and resources, and testing via the MCP Inspector and Claude Desktop.

An AI code audit server based on the local Ollama model. Through the integration of the Model Context Protocol (MCP), it provides multi - dimensional code analysis, including security, integrity, performance, quality, architecture, testing, and documentation checks.

The Enkrypt AI MCP Server is a server for integrating red team testing, prompt auditing, and AI security analysis. It is compatible with the Model Context Protocol (MCP) standard and supports functions such as real - time prompt risk analysis and adversarial prompt generation. It can be seamlessly integrated with MCP clients such as Claude Desktop and Cursor IDE.