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
A Model Context Protocol (MCP) server that uses the Osmosis-Apply-1.7B model to merge code edits.
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Drive KiCad schematic, PCB, DRC/ERC, DFM, and manufacturing review from any MCP-capable AI agent.
This repository contains Model Context Protocol (MCP) servers that provide various tools and capabilities for AI models.
A Model Context Protocol server that provides . This server enables LLMs to get search result information from Google.
🤖 A Model Context Protocol (MCP) library for use with Agentic chat bots
Wow! It's awesome, now you can use the MCP server of Rod!🚀
MCP 资源精选， MCP指南，Claude MCP，MCP Servers, MCP Clients
Zotero MCP: Connects your Zotero research library with Claude and other AI assistants via the Model Context Protocol to discuss papers, get summaries, analyze citations, and more.
A C++ implementation of a Model Context Protocol Server with a pluggable module architecture.
Model Context Protocol server for FTP access
A Model Context Protocol (MCP) server that provides AI-powered search and querying capabilities for the Vercel AI SDK documentation.
Agent Skills
The main repository for libraries used to build applications on the Atsign Platform. Three categories: SDKs, libraries, and Flutter widgets.
is an API-first Ruby web framework that combines the developer experience of Rails with fiber-based concurrency.
本项目是基于吴恩达老师在 DeepLearning.AI 平台推出的 agent-skills-with-anthropic 系列课程的中文学习资料整理项目。我们致力于为中文学习者提供高质量的课程内容翻译、系统的知识点梳理以及详细的示例代码解读，帮助大家更轻松地掌握 Agent Skills。
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upfetch is an advanced fetch client builder with standard schema validation, automatic response parsing, smart defaults and more.
A collection of Pi Coding Agent customized instances. Why? To showcase what it looks like to hedge against the leader in the agentic coding market, Claude Code.
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SkillsBench evaluates how well skills work and how effective agents are at using them.
Website • Getting Started • Documentation • Community
KAI Scheduler is a robust, efficient, and scalable Kubernetes scheduler that optimizes GPU resource allocation for AI and machine learning workloads.
An interactive five-chapter night walk through a Kyoto mountain temple, rendered live in Three.js.
For more advanced capabilities and end-to-end machine learning, visit www.k-dense.ai.