Claude Desktop インストールガイド
ローカル MCP 設定に対応するデスクトップクライアント。
MCP Servers

Give agents controlled browser sessions for research, QA, screenshots, and web tasks.

Volcengine MCP Servers

Lighweight CLI to interact with MCP servers

Model Context Protocol server for Task Management. This allows Claude Desktop (or any MCP client) to manage and execute tasks in a queue-based system.

Draw.io Model Context Protocol (MCP) Server

A Model Context Protocol (MCP) server that enables secure interaction with MySQL databases

One home for every agent. A free, open-source app to manage all your AI coding agents — desktop, CLI, or web.

Agent-MCP is a framework for creating multi-agent systems that enables coordinated, efficient AI collaboration through the Model Context Protocol (MCP).

Telegram MCP server powered by Telethon to let MCP clients read chats, manage groups, and send/modify messages, media, contacts, and settings.

FreeCAD MCP(Model Context Protocol) server

🧠 The AI-native memory framework for building intelligent, context-aware applications 🧠 Built with Rust, Cortex Memory is a high-performance, persistent, and intelligent long-term memory system...

A lightweight, rollbackable, and visual Long-Term Memory Server for MCP Agents. Say goodbye to Vector RAG and amnesia.
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.