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
Semantic Intelligence for Large-Scale Engineering. Context+ is an MCP server designed for developers who demand 99% accuracy.
Minimal MCP Server for Aider
CAD MCP Server
A macOS AppleScript MCP server
A model context protocol server to work with JetBrains IDEs: IntelliJ, PyCharm, WebStorm, etc. Also, works with Android Studio
MCP-NixOS - Model Context Protocol Server for NixOS resources
A Model Context Protocol server that executes commands in the current iTerm session - useful for REPL and CLI assistance
Community plugin to control Blender 3D with any LLM of your choice
5ire is a cross-platform desktop AI assistant, MCP client. It compatible with major service providers, supports local knowledge base and tools via model context protocol servers .
A flexible HTTP fetching Model Context Protocol server.
Context window optimization for AI coding agents. Sandboxes tool output (98% reduction), persists session memory, and enforces routing across 17 platforms via MCP + hooks.
A Model Context Protocol Server for Varlet UI Provides AI assistants with comprehensive access to Varlet UI documentation, component APIs, and development resources.
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.