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개발자용 MCP 서버와 함께 자주 쓰이는 AI 코드 에디터.
MCP Servers
Multi-agent code review mesh — orchestrates AI agents from multiple providers to review code in parallel, cross-review each other's findings, and build accuracy profiles over time.
Open-source infrastructure for AI agents — each gets an email address, folder, inbox, and API key. Move files through named inboxes instead of shared cloud credentials; signed receipts and MCP built...
local-first MCP discovery runtime for agents — search before invoke, reduce prompt bloat, and route to local MCP tools
Unify every AI agent on ONE local shared memory over MCP. Obsidian vault + gbrain (by Garry Tan) + Ollama. 100% offline, $0 API. Orchestrate with OpenClaw or Hermes.
A MCP server that connects to Stakpak API.
An MCP server that provides tools for sending and testing in sandbox via Mailtrap.
Production-ready MCP server for Kaiten API integration with Claude Desktop
between your team and your AI coding agents. Define your rules once. Enforced everywhere. Every session.
Composite MCP server for Godot Engine -- 17 composite tools for AI-assisted game development.
：这是一个刚刚开发的项目，功能仍在完善中，欢迎各位提出建议和改进！ : This is a newly developed project with features still being refined. Suggestions and improvements are welcome!
🌉 Local-first Proton Mail MCP and CLI through Proton Bridge. Search, read, draft, send, sync, and act on mail from Claude Desktop or Terminal.
[DEPRECATED] Unity MCP server — successor: akiojin/unity-cli
Agent Skills
This repository provides technical guidance for users and developers using Amazon EC2 instances powered by AWS Graviton processors (including the latest generation Graviton5 processors).
A curated list of delightful NoCode / LowCode applications and resources. For more awesomeness, check out awesome.
ThingLinks is an enterprise-grade built on Spring Cloud microservices architecture. It delivers device connectivity, supporting on a single node with plugin-based extensibility and multi-protocol...
本项目围绕吴恩达老师在 DeepLearning.AI 推出的 Agentic AI 系列课程，致力于为中文学习者提供高质量的课程内容翻译、系统化的知识梳理、关键概念解析以及配套示例代码的详细解读。项目不仅帮助学习者跨越语言障碍，更通过结构化整理与实践引导，深入理解“智能体”（Agent）在现代 AI 系统中的核心作用，掌握构建自主、协作、推理型 AI 应用的关键方法。
橙皮书 (Orange Book) Series · by HuaShu (花叔)