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
- Research Twitter and Post Twitter(https://www.youtube.com/watch?v=--QHz2jcvcs)
Phone numbers as tools. Your agent orders a private number in the country a service expects, reads the SMS verification code straight from the API, and hands the number back.
Permanent memory for AI agents. Single binary, zero dependencies, MCP native.
Your agents forget everything between sessions. MemMesh gives them durable, typed, searchable memory that lives on your machine — no vector database, no search cluster, no mandatory LLM calls.
Vite plugin that enables a MCP server helping models to understand your Vue app better.
MCP Server for COMSOL Multiphysics simulation automation via AI agents.
Semantic Code Intelligence for AI Coding Agents
Library for connecting AI agents to Todoist. Includes tools that can be integrated into LLMs, enabling them to access and modify a Todoist account on the user's behalf.
The official Redis MCP Server is a natural language interface designed for agentic applications to manage and search data in Redis efficiently
Entroly — The Open-Source Context OS for AI Agents
Lightweight MCP for AI agent browser automation. Record once, replay forever — cut token cost and speed up repetitive tasks.
Some users may see already installed with an old version when running brew upgrade claude-in-mobile. This happens when the local tap points to the wrong repository. Fix:
Agent Skills
This repository provides technical guidance for users and developers using Amazon EC2 instances powered by AWS Graviton processors (including the latest generation Graviton5 processors).
A curated list of delightful NoCode / LowCode applications and resources. For more awesomeness, check out awesome.
ThingLinks is an enterprise-grade built on Spring Cloud microservices architecture. It delivers device connectivity, supporting on a single node with plugin-based extensibility and multi-protocol...
本项目围绕吴恩达老师在 DeepLearning.AI 推出的 Agentic AI 系列课程，致力于为中文学习者提供高质量的课程内容翻译、系统化的知识梳理、关键概念解析以及配套示例代码的详细解读。项目不仅帮助学习者跨越语言障碍，更通过结构化整理与实践引导，深入理解“智能体”（Agent）在现代 AI 系统中的核心作用，掌握构建自主、协作、推理型 AI 应用的关键方法。
橙皮书 (Orange Book) Series · by HuaShu (花叔)