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.

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.

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.

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.

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.

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.

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.

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.

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.

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 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.

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.

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.

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.

The Okta MCP Server is an innovative tool based on the Model Context Protocol (MCP) that enables AI models to directly interact with the Okta environment. It provides a standardized AI integration solution for IAM engineers and security teams, supporting core functions such as user management and group operations. It is currently in the Alpha testing phase.

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.

The Go Development MCP Server is a solution that integrates the Go development workflow with AI assistants, supporting code compilation, testing, running, analysis, and multi-module workspace management. It enables intelligent development assistance through the Model Context Protocol.

A Django application that implements a Firebase Model Context Protocol (MCP) server, enabling AI agents to interact with Firebase services through a standardized protocol. It provides 14 Firebase tools covering authentication, database, and storage functions, supporting quick testing and full integration.

The Safari MCP server is a macOS tool based on the Model Context Protocol that provides programmatic control functions for the Safari browser, supporting web automation, testing, and AI-assisted debugging.

This project is a GitHub repository for testing and exploring the implementation of the Model Context Protocol (MCP) server, containing sub - projects related to learning multiple programming languages, DevOps tools, game development, and AI.