Zen MCP is a multi-model AI collaborative development server that provides enhanced workflow tools and cross-model context management for AI coding assistants such as Claude and Gemini CLI. It supports seamless collaboration of multiple AI models to complete development tasks such as code review, debugging, and refactoring, and can maintain the continuation of conversation context between different workflows.

Refact Agent is an open - source AI programming assistant that supports multi - language code generation, debugging, and optimization. It integrates with mainstream development tools, can be deployed locally, and provides intelligent code completion and code explanation functions.

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.

Inspektor Gadget MCP Server is an AI-driven debugging and inspection tool for Kubernetes clusters, providing one-click deployment, intelligent analysis, and automatic discovery functions.

The GDB MCP server is a tool that supports AI-assisted debugging, enabling interaction with GDB through the MCP protocol and simplifying multi-architecture and remote debugging processes.

LLDB-MCP is a tool that integrates the LLDB debugger with Claude's MCP protocol, enabling AI-assisted debugging functions

A Godot 4 example project containing an MCP client plugin, used to demonstrate real-time viewing, modifying scene node attributes, and calling methods through AI tools such as Claude during game runtime, enabling AI-assisted debugging and development.

defold-mcp is an open-source Model Context Protocol (MCP) server designed to connect the Defold game engine with modern developer tools and AI-assisted workflows. It provides a set of automation tools for managing Defold projects, generating scripts and resources, debugging and analyzing projects, and supports integration with AI development tools such as Cursor.

This project provides the Model Context Protocol (MCP) service for Apache Fineract®, supporting implementations in Python, Java, and Node.js, enabling AI agents to access financial data and operations. It includes a debugging tool, multi - language implementations, and standardized API interfaces.

dap-mcp is a DAP session management tool based on the MCP protocol, aiming to optimize and expand the context window of large language models and improve the debugging workflow.

MCP-openMSX is a bridge project that connects modern AI development with retro computing (MSX systems). It provides a comprehensive control toolset for the openMSX emulator through the MCP protocol, including emulator management, media operations, BASIC programming support, debugging tools, and automation functions.

This project is an MCP server integrated with the Stable Diffusion image generation function, providing image generation services for AI agents. It supports generating images through the MCP protocol or direct API calls and includes development and debugging tools.

The GDAI MCP Godot plugin is a tool that allows AI to remotely control the Godot engine editor via the MCP protocol, supporting functions such as automated scene creation, node creation, script writing, and debugging.

BrowserLoop is a Playwright-based MCP service tool for automatically capturing web page screenshots and monitoring console logs, supporting AI agents in web debugging, testing, and development tasks.

This project is a Python tutorial practice on how to create an MCP server. You can add and manage the MCP server through the Claude command-line tool, and it supports testing and debugging of AI functions such as the ChromaDB vector database.

An AI knowledge base and data processing project that includes vector database processing, MCP protocol support, and core function libraries, supporting text chunking, vectorized search, and debugging tools.

This project is an MCP server integrated with Stable Diffusion image generation functionality, providing image generation services for AI agents, including development and debugging tools and Goose platform integration capabilities.

Overview: The Model Context Protocol (MCP) is a protocol designed to enable AI agents to access and utilize context, tools, and prompts. It allows for the creation of servers that provide standardized interfaces to interact with local or remote services, thereby enabling automated workflows such as reading files, operating databases, debugging code, and pushing changes to GitHub.

This is an MCP server that connects to the Coreflux MQTT broker, providing Coreflux and MQTT operation tools for AI assistants such as Claude. It includes a configuration assistant, debugging functions, and various operation instructions.

The Roblox Studio MCP Server is a powerful AI - assisted development tool that enables game project analysis, script debugging, and batch editing operations through 18 professional functions, connecting the AI environment with the Roblox Studio workflow.

Overview: MCP (Model Context Protocol) is a framework for AI automation through a standardized protocol, which includes key components such as hosts, clients, servers, local data sources, and remote services. The core lies in the server, which provides context, tools, and prompts for clients. MCP enables AI agents to automate tasks, such as code generation, debugging, and interaction with external services like GitHub repositories.

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 is a server - side project that implements the Model Context Protocol (MCP). It supports AI assistants to interact with external services and data sources, is compatible with AI assistants such as Claude, and provides task creation, debugging tools, and development guides.

A tool that provides Python breakpoint debugging capabilities through the MCP protocol, supporting CLI and AI assistant integration, and implementing production-level debugging functions using the DAP protocol.

BrowserTools MCP is a powerful browser monitoring and interaction tool that enables AI applications to capture and analyze browser data through a Chrome extension, supporting multiple audit and debugging functions.