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

An MCP (Model Context Protocol) server that enables integration between AI assistants (Claude, GPT, and other MCP-compatible tools) and FreeCAD, allowing AI-assisted development and debugging of 3D...

Enhanced Model Context Protocol (MCP) server for programmatic CAD modeling with Onshape.

A Model Context Protocol (MCP) server that provides tools for reading and extracting text from PDF files, supporting both local files and URLs.

inspiration from https://github.com/mark3labs/mcphost

An MCP interface/extension for Jupyter Server

A Model Context Protocol (MCP) server implementation that integrates Nuclei, a fast and customizable vulnerability scanner, with the MCP ecosystem.

MCPHub is an embeddable Model Context Protocol (MCP) solution for AI services. It enables seamless integration of MCP servers into any AI framework, allowing developers to easily configure, set up,...

A comprehensive Model Context Protocol (MCP) server for molecular dynamics simulations using OpenMM and DFT calculations with Abacus.

A Model Context Protocol (MCP) server for searching and retrieving Solodit vulnerability reports.

From AI Assistance to Agentic Workflows: Making MCP Practical in the Browser

Enhanced MCP code execution. Agent framework-agnostic (optimized for Claude Code). Skills framework (99.6% token reduction), multi-transport, sandboxing

A production-grade OCR server built using MCP (Model Context Protocol) that provides OCR capabilities through a simple interface.
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: