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
MCP server for external memory layer for AI agents + more . Download from pypi , and get started
Give an AI agent hands-on control of Blender: build geometry, apply materials, render, and check that a mesh is printable — 98 tools over the Model Context Protocol.
Connect AI assistants to your terminal with full control — 36 MCP tools including SFTP support
Essential random number generation utilities from the Python standard library, including pseudorandom and cryptographically secure operations for integers, floats, weighted selections, list...
MCP server that gives AI agents instant codebase understanding via the Supermodel API. Pre-computed code graphs enable sub-second responses for symbol lookups, call-graph traversal, and...
MCP server for Taiwan's largest job platform — search jobs, browse companies, and apply, all from Claude.
The watchman for your local AI agents' MCP layer.
A MCP server that connects to Stakpak API.
between your team and your AI coding agents. Define your rules once. Enforced everywhere. Every session.
One-Click MCP Configuration Sync Tool. 中文
：这是一个刚刚开发的项目，功能仍在完善中，欢迎各位提出建议和改进！ : This is a newly developed project with features still being refined. Suggestions and improvements are welcome!
MCP server for Cosense (formerly Scrapbox).
Agent Skills
AetherViz Master - 互动教育可视化建筑师，将任意教学主题转化为沉浸式3D交互网页
HEY CLI and Agent Skills
High-performance AI coding agent CLI written in Rust with zero unsafe code
A visual tool to edit HTML and Markdown files, leave comments like a Google Doc, and send feedback to your AI agent. Works inside your favorite AI harness.
A multi-agent workflow system for GitHub Copilot in VS Code that brings structure, quality gates, and long-term memory to AI-assisted development.
Generate realistic synthetic security logs for cybersecurity threat hunting training and research.
A comprehensive development toolkit designed following Anthropic's Claude Code Best Practices for AI-assisted software development.
Powered by , this project orchestrates 14 , each modeled after world-class experts in their domain. They ideate products, make decisions, write code, deploy, and market - without human intervention.
The Pi extensions and skills I use to keep long agent sessions useful without building a fake operating system around them.
Tell your coding agent to do real, multi-step work, then Smithers runs it for minutes or days: watch every step live, gate the risky ones behind human approvals, and rewind, fork, or replay any run.
[Documentation] [Quick Start] [简体中文] [Tiếng Việt]
An open standard for shared agent learning. Agents persist, share, and query collective knowledge so they stop rediscovering the same failures independently.