Cursor 설치 가이드
개발자용 MCP 서버와 함께 자주 쓰이는 AI 코드 에디터.
MCP Servers
This MCP server enables dynamic creation, editing and saving of PowerPoint presentations. Built upon the MCP and using the python-pptx library, it provides a flexible interface to add slides, images,...
This is an example of an application that's exclusively accessible via Model Context Protocol (MCP).
kali linux mcp,pentest,penetration test
built by an autonomous agent · sibyl labs llc
Enhanced note taking for AI Agents with supervision.
Turn any OpenAPI spec into a native CLI binary. No MCP, no bloat, no runtime dependencies, ONLY CLI.
Persistent, local, cross-IDE memory for AI agents — markdown source of truth, LanceDB-powered semantic search, zero cloud dependency
- Let AI assistants analyze binaries directly
Fictional concept interface—not an actual Codex UI or a measured context, token, speed, or latency benchmark.
Persistent memory system for agentic AI via MCP - remember, recall, forget with semantic search with knowledge graph
Perplexity Advanced MCP is an advanced integration package that leverages the OpenRouter and Perplexity APIs to provide enhanced query processing capabilities.
A CLI tool for managing MCP servers configurations for MCP clients.
Agent Skills
One command. 25 agent skills. Zero to profitable business.
AI video generation skills for Claude Code, Cursor, and OpenClaw. Auto model selection across 10+ models. Text, images, URLs, scripts, or audio in — finished video out.
JSON spec -> .excalidraw + .png + animated .gif
Open-source, local-first video editor where creators and AI agents edit the same real timeline.
“论文不是把字堆满，而是把项目事实、样文规范、图表截图和 Word 交付一次性闭环。”
A collection of Agent skills and Claude Code plugins for HashiCorp products.
A Next-Gen AI Agent Platform & Desktop Control Plane 中文文档 | Features | Getting Started | Architecture
即梦 是字节跳动的多模态 AI 视频生成模型，支持图片 / 视频 / 音频混合输入，可生成 4–15 秒的高质量视频。
帮你在 AI 时代找到**的兼职/副业。核心不是"列一堆项目"，而是四件别人不做的事：
这里不是一叠孤立的提示词。每个 Skill 都用 SKILL.md 固化触发条件、工作阶段、确认门槛和交付物，让 Codex、Claude Code 等 Agent 在产品、开发、研究、写作和日常效率任务中按同一套方法工作。
Generate and evaluate agent skills based on traces with agents. Create skills with teacher models (expensive/slow) that student models (cheap/fast) can use to perform harder tasks reliably.
The central challenge in AI development isn't a lack of ideas, but the inconsistent process of turning them into robust, reliable skills.