Claude Desktop 설치 가이드
로컬 MCP 설정을 지원하는 데스크톱 클라이언트.
MCP Servers
A Model Context Protocol server that provides knowledge graph management capabilities. This server enables LLMs to create, read, update, and delete entities and relations in a persistent knowledge...
Monitor browser logs directly from Cursor and other MCP compatible IDEs.
MCP server for Atlassian tools (Confluence, Jira)
Build effective agents using Model Context Protocol and simple workflow patterns
MCP server for interfacing with Godot game engine. Provides tools for launching the editor, running projects, and capturing debug output.
The fullstack MCP framework to develop MCP Apps for ChatGPT / Claude & MCP Servers for AI Agents.
This is a TypeScript-based MCP server that implements a simple notes system. It demonstrates core MCP concepts by providing:
A Model Context Protocol server that provides debugging functionality for both GDB and LLDB debuggers, for use with Claude Desktop, VSCode Copilot, or other AI assistants.
A Model Context Protocol server for PostgreSQL databases. Enables LLMs to query and analyze PostgreSQL databases through a controlled interface.
Model Context Protocol (MCP) server for Hostinger API.
Model Context Protocol server for the - uncensored, private AI for any MCP host (Claude Desktop, Cursor, ChatGPT, LM Studio, Continue, LibreChat, Open WebUI, AnythingLLM, Jan, Le Chat).
Think DVWA but for MCP/AI agent security.
Agent Skills
🌐 Make websites accessible for AI agents. Automate tasks online with ease.
the runtime your coding agents live on
Small, composable skills for coding agents.
Think package.json, requirements.txt, or Cargo.toml — but for AI agent configuration.
The official Lark/Feishu CLI tool, maintained by the larksuite team — built for humans and AI Agents.
Personal dotfiles with modern shell tooling, optimized for Laravel/PHP development. Features fast startup times, smart directory navigation, and modern CLI tools.
Building AI agents, atomically
Режим идиоматического русского мата для AI-агентов. Короче, душевнее, эффективнее. 18+
Open-source, local-first desktop AI research workbench for scientific computing with Python/R, MCP bioinformatics tools, SSH/WSL/GPU runtimes, and OpenAI/Anthropic models.
Autonomous research system for measurable, computer-executable research.
LLM-compiled knowledge bases for any AI agent. Parallel multi-agent research, collector catalogs, automated session capture, feedback curation, thesis-driven investigation, source ingestion, wiki...
You don't write AGENTS.md. You train it with gradient descent.