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
1. GET ACTIONS: Exposes APIs to fetch the most relevant content from InterviewReady including blogs, resources and course materials. 2.
Yet Another Frida MCP Server - Full-featured MCP server for Frida dynamic instrumentation
Hosted uptime monitoring and public status pages for teams. Multi-region checks, automatic incidents, on-call alerts (Slack/Telegram/webhook/+), subscribers, REST API, Terraform provider, MCP server.
MCP Server for the Bitrise API, enabling app management, build operations, artifact management, and more.
Real reap --agent output, run against a generated sample stack ( hero-fixture.sh ) — not anyone's install. The numbers further down are measured on mine.
A mcp server that bridges Dune Analytics data to AI agents.
This MCP server connects your AI agent to — Google's creative suite for image and video generation. Your agent can:
This is an example of an application that's exclusively accessible via Model Context Protocol (MCP).
Please see the updated mcpb format Claude Desktop Extension
Use Devnors Data from Python with one API Key.
Self-hosted, agent-native web app and MCP server for your Obsidian-style Markdown vault. Browse, search, and edit notes from a fast UI or from AI agents.
AI 端到端开发 Cocos Creator 3.8 游戏 — 42 个 MCP 工具 + Claude / Codex / Cursor Skill
Agent Skills
The Best AI Agent Framework for Agent Collaboration.
The open sharing protocol for the agentic era. A Linux Foundation AI & Data Project
Agent Skills
- : Turn your idea into a video using your coding agent. - : Edit and animate using drag and drop. - : Connect to data, and manage complexity with code.
Reverse-engineer any design system into a Claude-ready skill. Pure static analysis. No AI. No API keys.
Craft AI-driven interface effortlessly🤖
Official Pulumi Agent Skills for writing, migrating, and operating infrastructure with AI coding agents
- [2026/05/01] 🔥 (📃Paper) has been released.
A Claude Code of the skills we share at AI Builder Club for building : agents that get triggered on their own, pick up work, ship it, verify it, and log what they learned, so the work compounds...
"To achieve great things, two things are needed: a plan and not quite enough time." - attributed to Leonard Bernstein
Commonplace studies how agentic systems can change after deployment through inspectable knowledge artifacts.
LiteRT-LM is Google's production-ready, high-performance, open-source inference framework for deploying Large Language Models on edge devices.