Claude Desktop Руководство установки
Десктопный клиент с поддержкой локальной конфигурации MCP.
MCP Servers
MCP Fundamentals 🧱 Meet users in the AI apps they already use Your users are increasingly getting accustomed to using natural language to communicate with AI apps like ChatGPT, Claude Desktop, and...
Your senior Microsoft 365, Intune, and Entra admin, installed in the AI client you already use. Agent Skills plus MCP servers for Claude Code, Cursor, Codex, Gemini, and GitHub Copilot, with a human...
CLI + Local MCP - A shared structured memory store across Claude Code, Cursor, Windsurf, Antigravity, and every MCP client. Semantically queryable.
Living Memory Architecture for Autonomous AI Agents — MCP server with typed connections, beliefs, decay, reconsolidation
One command. TypeScript Python. Example tools, the Inspector, and tests — all wired up. Or point it at an OpenAPI spec and get
The local-first knowledge layer for AI development.
A Stdio MCP server which proxies an SSE MCP server.
An MCP server for Basecamp 3. It lets MCP-capable clients such as Codex, Cursor, and Claude Desktop read and manage Basecamp projects through OAuth-authenticated Basecamp API calls.
A starting point for Claude Code to Codex collaboration
Local-first knowledge compiler for humans and agents. Inspired by Karpathy's vision. Plain markdown, CLI + MCP server.
The cognitive memory layer for AI agents.
Generic markdown vault MCP with hybrid search
Agent Skills
Agent skills extracted from real work. Each one shipped something first.
Personal Codex skills (drop-in folders under ~/.agents/skills/). Catalog: https://jmerta.github.io/codex-skills/
Open the interactive guide to learn more about the Skill
The open agent skills tool - npx skills
A curated list of essential skills, tools, and resources for building and enhancing advanced AI agents.
Keep your skills sharp. Intelligence for agent context.
Chainstack is the leading suite of services connecting developers with Web3 infrastructure
A structured Agent workflow for CUMCM, MCM/ICM, and Diangong Cup — designed to keep a 72–96 hour modeling project coherent from the first decision to the final submission.
会话 · 聊天记录 · 搜索 · 联系人 · 群成员 · 群昵称 · 收藏 · 统计 · 导出
🧠 plan · 🔨 implement · 🔍 review · ✅ QA gate · 🚢 merge Thirty-five agent skills that run a full PR pipeline. Install them into any repo, with any coding agent.
for creating, directing, validating, and delivering image, video, audio, voice, music, 3D, avatar, and interactive media.
Running 5 AI agents in parallel is easy. Making them not break each other's code is the hard part.