Cursor Install Guide
AI code editor frequently used with developer-focused MCP servers.
MCP Servers
is a minimalist implementation of agents powered by LLMs and Model Context Protocol (MCP) tools.
A testing suite and reference implementation for the Model Context Protocol (MCP).
We build reliable servers thoughtfully designed for MCP Client-powered workflows.
Kernel-level sandboxing for LLM agent tool calls made through the Model Context Protocol (MCP).
"The question is not what you look at, but what you see." — Henry David Thoreau
Ollama MCP is a tool for connecting Ollama-based language models with external tools and services using the Model Context Protocol (MCP).
mcp4k is a compiler-driven framework for building both clients and servers using the Model Context Protocol (MCP) in Kotlin.
This is a Model Context Protocol (MCP) server that converts Figma designs to React components. It provides tools for fetching Figma designs and generating React components with TypeScript and...
The Model Context Protocol enables AI models to interact with external systems through tools, resources, and prompts.
An example personal assistant built with Mastra and MCP (Model Context Protocol) that helps with various daily tasks and information management.
A TypeScript library that bridges OpenAI's Realtime API with Model Context Protocol (MCP) servers, enabling voice-driven tool execution.
This repository contains implementations of the Model Context Protocol (MCP), an open standard that connects AI systems with external tools and data sources.
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：