Claude Desktop インストールガイド
ローカル MCP 設定に対応するデスクトップクライアント。
MCP Servers
Self-hostable, MCP-native testing platform. Manual test management, deterministic runs, optional AI. Your stack, your LLM, your data.
MCP server that generates ATS-friendly CVs, cover letters, and email templates tailored to any job description
MCP server providing code intelligence using static analysis
Convert PDF, Word, PowerPoint, HTML, email & 40+ formats to clean Markdown — and back. Built for LLMs, RAG & Python pipelines, with a built-in MCP server.
🦀 High-performance local RAG server in Rust that integrates with Claude Desktop via MCP. Search PDF documents privately using Ollama embeddings - no external API calls.
Model Context Protocol (MCP) server for JetBrains TeamCity: control builds, tests, agents and configs from AI coding assistants.
MCP server for UPS APIs
DocSpace MCP Server
Expose, secure, and observe MCP servers — from your laptop to production clients.
agentic-obs: A Model Context Protocol (MCP) server that provides AI assistants with programmatic control over OBS Studio via the OBS WebSocket API.
Multi-agent orchestration via MCP. Persistent memory, inter-agent messaging, goal cascade, context budget pruning. One binary, zero config.
Drive the Chrome you are already logged into - from your terminal or any AI assistant. Cross-platform, MCP-ready.
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.