Claude Desktop 설치 가이드
로컬 MCP 설정을 지원하는 데스크톱 클라이언트.
MCP Servers
Showing how to transition from a naive agent to an MCP agent in 3 steps
A remote Cloudflare MCP server boilerplate with user authentication and Stripe for paid tools.
A collection of MCP (Model Context Protocol) servers for managing and integrating (LLM) various Large Language Model services.
Building MCP servers with Delphi
This project demonstrates how to build interactive MCP (Model Context Protocol) widgets that run on Cloudflare Workers and can be embedded in AI chat interfaces like ChatGPT.
This project implements a small team of coding agents using LangGraph and the Model Context Protocol (MCP). The agents use MCP servers to provide tools and capabilities through a unified gateway.
Look, a flock of geese! An MCP server and protocol for Goose agent collaboration.
A production-ready for seamless integration between Wazuh SIEM and Large Language Models (LLMs).
Agentic RAG with MCP Server
A practical implementation demonstrating ADK (Agent Development Kit) as an MCP (Model Context Protocol) client for flight search capabilities.
Welcome to ntfy-mcp, the MCP server that keeps you caffeinated and informed! 🚀☕️
A simple and clear example for implementation and understanding Anthropic MCP (on AWS Bedrock).
Agent Skills
AetherViz Master - 互动教育可视化建筑师，将任意教学主题转化为沉浸式3D交互网页
HEY CLI and Agent Skills
High-performance AI coding agent CLI written in Rust with zero unsafe code
A visual tool to edit HTML and Markdown files, leave comments like a Google Doc, and send feedback to your AI agent. Works inside your favorite AI harness.
A multi-agent workflow system for GitHub Copilot in VS Code that brings structure, quality gates, and long-term memory to AI-assisted development.
Generate realistic synthetic security logs for cybersecurity threat hunting training and research.
A comprehensive development toolkit designed following Anthropic's Claude Code Best Practices for AI-assisted software development.
Powered by , this project orchestrates 14 , each modeled after world-class experts in their domain. They ideate products, make decisions, write code, deploy, and market - without human intervention.
The Pi extensions and skills I use to keep long agent sessions useful without building a fake operating system around them.
Tell your coding agent to do real, multi-step work, then Smithers runs it for minutes or days: watch every step live, gate the risky ones behind human approvals, and rewind, fork, or replay any run.
[Documentation] [Quick Start] [简体中文] [Tiếng Việt]
An open standard for shared agent learning. Agents persist, share, and query collective knowledge so they stop rediscovering the same failures independently.