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
📣 🎉 It is hosted by Qonto, authenticates via OAuth, and supports both read and write operations. Learn more at mcp.qonto.com.
"Reduce system lag by 99%, eliminate loading times, and cut token costs by 90%."
I've been running this Gemini MCP server in my Claude Desktop setup for months. It's one of the few I leave on permanently — not because Gemini replaces Claude, but because grounded search, image...
MCP server for CLO3D. Control 3D garment design from Claude, Cursor, or any MCP client.
MCP server with 55 security intelligence tools — CVE/KEV, MITRE ATLAS+D3FEND, Sigma detection rules, email security posture (SPF/DMARC), domain & web intel, threat intel.
基于 SunnyNet 中间件和 SunnyNetTools 抓包工具扩展的 MCP Server
The jMRI (jMunch Retrieval Interface) specification — an open interface standard for token-efficient context retrieval in MCP servers.
MCP-сервер для прямой работы с клиентом тестирования без менеджера тестирования
An MCP server that enables searching for Rust crates and their documentation from crates.io and docs.rs.
Persistent memory and codebase intelligence for AI coding agents, indexes symbols, tracks sessions, and exposes structured project knowledge through an MCP server so agents stop re-reading files and...
gotoHuman makes it easy to add to AI agents and agentic workflows. A fully-managed async human-in-the-loop workflow with a customizable approval UI.
A comprehensive and efficient MCP server for task management with multi-format support (Markdown, JSON, YAML)
Agent Skills
This project is under active development and evolving rapidly. Contributions, feedback, and discussions are warmly welcome.
Agent skill that audits vibe-coded apps for common security vulnerabilities introduced by AI coding assistants
A high-performance Markdown parser and renderer for Angular, React, Svelte, Vue, HTML and ANSI.
A collection of Codex/agent skills for planning, documentation access, frontend development, and browser automation.
简单说，就是跟 Claude 说一句话，它会帮我从每天的新论文里筛一轮，挑出值得看的，再把重点论文读完、写成 Obsidian 笔记。日常不用记一堆命令，基本就是：