Cursor 安装指南
常与开发类 MCP Server 搭配使用的 AI 代码编辑器。
MCP Servers
AdaptixC2 MCP Server — Model Context Protocol server that enables AI agents to interact with AdaptixC2 through MCP.
A Model Context Protocol server for DuckDuckGo Search
A server to integrate with Anki via the AnkiConnect plugin
MCP Server Playwright A Model Context Protocol server that provides browser automation capabilities using Playwright Enable LLMs to interact with web pages, take screenshots, and execute JavaScript...
A Model Context Protocol (MCP) server for AFFiNE. It exposes AFFiNE workspaces and documents to AI assistants over stdio (default) or HTTP (/mcp) and supports both AFFiNE Cloud and self-hosted...
mem-agent mcp server
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools.
A powerful MCP server for generating, editing, and converting SVG images using SVGMaker API.
🧠 Project-Centric 📊 Relationship Graphs ⚡ High Performance One database per project Intelligent code connections Minimal resource needs
Model Context Protocol server providing comprehensive code analysis, navigation, and quality assessment capabilities .
BlockbenchMCP connects Blockbench to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blockbench.
This monorepo provides a suite of tools that bridge AI agents with Mock Service Worker (MSW). It enables dynamic addition, updating, and removal of MSW network mocks directly from a command-line...
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：