Claude Desktop 설치 가이드
로컬 MCP 설정을 지원하는 데스크톱 클라이언트.
MCP Servers
A local MCP server that gives Claude a durable reading room:
is a professional MCP server for PostgreSQL database operations, monitoring, and management. Supports PostgreSQL 12-18 with comprehensive database analysis, performance monitoring, and intelligent...
Sub-millisecond, local-first, open source — the "open source Aspose."
JLCPCB PCBA向けの、部品探しを補助するためのMCPサーバー
Define TypeScript capabilities that send emails, manage calendars, and automate work. Expose them to the Routecraft agent, Claude, ChatGPT, Cursor, or any AI agent via MCP.
is a feature-complete MCP server for Huly integration. Published on npm as @firfi/huly-mcp.
Windows Computer Use for AI Agents. Both a tool (22 MCP tools for click, type, screenshot, OCR, UI inspection) and an agent (autonomous mission engine, macro recorder, intent-based discovery, event...
A companion repository to my video about MCP server for the robot: - for LLM-based AI agents (Claude Desktop, Cursor, Windsurf, etc.
Query and manage your personal finances with AI using local Copilot Money data
Live editing · Tracked changes · Per-action undo · 124 tools · Cross-platform
An MCP server that enables LLMs interacting with your network devices
MCP server that runs shell commands. Your LLM gets a tool; you get control over what runs and how.
Agent Skills
A personal library of Claude Code skills — installable prompt extensions that give Claude Code new capabilities.
From TypeScript Source → Rebuilt in Python with ❤️
一个用于 AI 编程助手的社交媒体发布技能，基于 agent-browser 实现自动化发布内容到各大社交平台。
大多数 AI 翻译生硬、欧化、一眼就能看出是机翻。**专为书籍级长文本设计，核心承诺是**。
📦 本仓库已收录至 openclaw-skills（聚合仓库，包含更多 Skills）。推荐 Star 聚合仓库以获取全部更新。
See the Kocoro product site for the current product demo.
A simple testing framework for bash scripts
Feed your AI something healthier than Markdown. allium-lang.org
把课程材料变成可持续学习、可反馈、可复习、可沉淀的 Obsidian 学习系统。
Skills shared by Canghe for improving daily work efficiency with Claude Code.
CatchMe: Make Your AI Agents Truly Personal
Empirically detect the repetitive defaults a model falls back on, then turn those findings into a reusable instruction file that makes future outputs less generic.