Cursor Install Guide
AI code editor frequently used with developer-focused MCP servers.
MCP Servers
MeteoSwiss Open Data — Python API, CLI & MCP server · tabular as DataFrames/Parquet, gridded as xarray/Zarr
AI-powered CLI and MCP server for browsing GitHub project documentation (unofficial tool)
Connect to MCP servers right from your shell. Plugin for simonw/llm.
CROW - Your AI Agent. MCPs, OpenRouter, Any Model or local. It's your choice.
Python implementation for building Users Management Agent with MCP tools and MCP server
Autonomous DFIR agent — SANS SIFT Workstation MCP server for incident response
基于 eryu（耳屿） © Evelyn & River 二次改作（有改动）， 依原项目协议以 CC BY-NC-SA 4.0 开源，。 纯 Python 标准库 + 原生 JS，零依赖，只需要一条命令就能跑。
轻便的人机共读MCP
A minimal MCP server built on crawl4ai for LLM-friendly web extraction
MCP Server for executing PowerShell scripts
Production-grade vector memory MCP server for Claude Code. Semantic search, per-project isolation, rules enforcement, team sharing via git.
A Claude Code skill + MCP server setup for expert-level Google Ads campaign analysis
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.