Claude Desktop 설치 가이드
로컬 MCP 설정을 지원하는 데스크톱 클라이언트.
MCP Servers
Welcome to the Kanban MCP project! 🎉 This project integrates Planka kanban boards with Cursor's Machine Control Protocol (MCP) to enable AI assistants like Claude to manage your kanban boards.
An MCP server to create, manage and publish X/Twitter posts directly through Claude chat.
MCP server that connects Claude to Cavalry animation software. Create layers, set attributes, animate with keyframes, render frames, and more — all through natural language.
Issue tracking for the agentic coding era. One binary. One SQLite database (plus an attachments dir). MCP built in.
An MCP server that provides programmatic access to Apple Mail, enabling AI assistants like Claude to read, send, search, and manage emails on macOS.
AI assistants are powerful, but they struggle with Kubernetes because:
Wavelet-based multi-resolution context management for LLMs via MCP.
- — Every memory save commits your entire project. Roll back anytime. - — CLAUDE.md loads instantly, deep store searchable mid-conversation.
A command-line interface for MCP servers. curl for MCP.
"Reduce system lag by 99%, eliminate loading times, and cut token costs by 90%."
Custom multi-agent system, no LangChain · public evals with the weak scores kept in · live in production
Claude Code, Cursor, Codex, and every other MCP client forget everything when a session ends. LLM Wiki Memory fixes that: it captures your conversations, compiles them into durable project knowledge...
Agent Skills
https://github.com/user-attachments/assets/023c0a9c-194a-45a9-bb88-ac8f16f5ffd5
Screenshot testing is key to validate your app's appearance and functionality. It efficiently detects visual issues and tests the app as users would use it, making it easier to spot problems.
Built by DeepSeek, for DeepSeek. An AI coding agent that flows through your codebase like a tide. The name: DeepSeek + tide (terminal IDE).
山音超级编剧大师 - 全格式影视编剧 Skill 由 @山音 设计的自然语言驱动编剧 Agent Skill 覆盖 1-3 分钟概念超短片→90 分钟电影长片→多集剧集的全流程剧本创作，一站式搞定人物、大纲、场景、剧本全链路
for quasi-experimental designs in Python.