Cursor インストールガイド
開発者向け MCP サーバーとよく使われる AI コードエディタ。
MCP Servers
The AI agentic designer — open-source React design system + MCP that lets Claude, Codex, Cursor & Gemini build production UI in minutes. No AI slop.
Chat with AI, run tasks on autopilot, and manage your projects — all from one tab.
Local-first persistent memory for Claude Code & Codex CLI - Rust CLI, hooks, MCP server, SQLite/SQLCipher, auditable recall for long-running coding work.
Roblox Studio MCP server & plugin for Claude Code, Cursor, Codex, and Gemini. AI-powered scripts, terrain, assets, lighting, and bidirectional project sync.
Claude Code rewritten in Go.. High-performance AI agent harness runtime in Go. MCP server, CLI tool orchestration, session management, Kiro integration. Single binary, zero dependencies.
Living Memory Architecture for Autonomous AI Agents — MCP server with typed connections, beliefs, decay, reconsolidation
AI-powered penetration testing MCP server
The ngrok alternative with .local domains, a scriptable CLI, and an MCP server for AI agents
Enhanced note taking for AI Agents with supervision.
Turn any OpenAPI spec into a native CLI binary. No MCP, no bloat, no runtime dependencies, ONLY CLI.
Every local AI coding session in one tab: Claude Code, Codex and OpenCode in a single list, with a queue you can schedule and isolated Claude Desktop instances kept apart. Local, private, MCP-native.
Persistent memory system for agentic AI via MCP - remember, recall, forget with semantic search with knowledge graph
Agent Skills
Agent Harness · Spring Boot inside · One JAR to ship
Pure python3 implementation for working with iDevices (iPhone, etc...).
从多项目日常使用中提炼的 Claude Code 工作流模板——涵盖记忆管理、上下文工程与任务路由。
An open-source biomedical AI research assistant built on OpenClaw and Claude Code, integrating 140 K-Dense Scientific Skills for bioinformatics, drug discovery, clinical research, and more.
dotagents One canonical .agents folder that powers all your AI tools.
This repository contains hands-on tutorials for learning LangChain, LangGraph, and Deep Agents, organized into two learning tracks:
A self-improving product system that reads daily reports, identifies the #1 actionable priority, and autonomously implements it.
Modern agents are not "a prompt + a tool." They are — with identity, memory, skills, tools, MCP integrations, guardrails, observability, evals, and a provider strategy.
Analysis, Comparison, Trends, Rankings of Open Source Software, you can also get insight from more than 10 billion with natural language (powered by LLM). Follow us on Twitter: https://twitter.
Platform design skill pack: 450+ rules for Apple HIG, Material Design 3, and WCAG 2.2 across iOS, iPadOS, macOS, watchOS, visionOS, tvOS, Android, and Web.
The practical guide to building AI agent harnesses — with real code examples you can copy and run.
本书围绕 DeerFlow 2.0，从理论到源码，系统讲解如何进行二次开发。 所有代码示例均基于真实源码，确保与 DeerFlow 实现保持一致。