Browse AI & ML model integration MCP servers. Connect Claude and other agents directly to Hugging Face, OpenAI, and specialized ML pipelines.
Discover the world's most comprehensive directory for AI Agent Skills and community-driven MCP Servers (Model Context Protocol). Seamlessly find and install high-quality developer integrations for your Claude Desktop, Cursor, or custom AI agents. From cloud operations to API integrations, explore verified open-source MCP practices to supercharge your AI workflows.
component-refactoring is an AI agent skill that refactors high-complexity React components in the Dify frontend. It is activated when `pnpm analyze-component --json` shows a complexity score over 50 or a line count exceeding 300, or upon direct user request for code splitting.
The most comprehensive Claude Code skills registry | Web Search: https://skills-registry-web.vercel.app
The most comprehensive Claude Code skills registry | Web Search: https://skills-registry-web.vercel.app
Unified multi-agent skill system for AI coding assistants (Claude Code, Cursor, Copilot, Gemini) with 414+ skills, 38 agents, and 57 commands. Features smart tech detection, per-project installation, and auto-sync from upstream sources.
66 Specialized Skills for Full-Stack Developers. Transform Claude Code into your expert pair programmer.
The most comprehensive Claude Code skills registry | Web Search: https://skills-registry-web.vercel.app
pair is the process layer for AI-assisted development. It gives your AI assistant the context, guidelines, and skills to work the way your team works.
gemma_domain_trainer_prototype is a skill that enables fine-tuning of Gemma 270M on domain-specific data using 0102 artifacts.
270+ Claude Code plugins with 739 agent skills. Production orchestration patterns, interactive tutorials (11 Jupyter notebooks), and CCPI package manager. 4.13.0
270+ Claude Code plugins with 739 agent skills. Production orchestration patterns, interactive tutorials (11 Jupyter notebooks), and CCPI package manager. 4.13.0
airbyte-agent-connectors is a set of standalone Python packages enabling AI agents to call third-party APIs through a secure and well-documented interface.
Evaluating-llms is a skill that evaluates Large Language Model systems using automated metrics, LLM-as-judge patterns, and standardized benchmarks