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-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.

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.

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 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.

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.

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

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

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.

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

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.

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.

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.

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 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.

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.

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

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.

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.

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 Model Context Protocol server for DICOM connection testing

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

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.

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

The Locust-MCP-Server is a load testing server based on the Model Context Protocol framework, supporting seamless running of Locust performance tests through an AI development environment, providing configurable test parameters and real-time execution output.

This project implements a CityGML data access server based on the Model Context Protocol (MCP), providing functions such as echo testing, HTTP services, and client examples.

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.

MockLoop MCP is the world's first AI-native API testing platform integrating the Model Context Protocol (MCP). It revolutionizes API testing through AI-driven scenario generation, automated test execution, and intelligent analysis capabilities. The platform offers 5 AI prompts, 15 scenario resources, 16 testing tools, and 10 context tools, supports a dual-port architecture and stateful testing workflows, and is suitable for enterprise-level compliance and advanced analysis requirements.

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.

Shioaji-MCP is a model context protocol server based on the Shioaji API, providing functions for development environment configuration and operational testing.

MCP Appium is a service that integrates Appium into the Model Context Protocol, allowing AI agents to automatically control and test mobile devices, supporting automatic server startup, device detection, and flexible testing.

This project is a dedicated repository for testing the GitHub Model Context Protocol (MCP), mainly verifying the interaction functions between AI models and GitHub services, including repository management, issue tracking, and content operations such as the PR process.