Tools

Has the agent build single-file HTML interactive playgrounds: visual controls on one side, live preview on the other, and a prompt to copy back into Claude. Templates for design tuning, data exploration, concept maps, doc annotation, code review and architecture diagrams. By Anthropic.

Official Anthropic plugin that reads local session logs in ~/.claude/projects and generates an interactive HTML usage report covering tokens, cache hit rate, subagents, skills and the most expensive prompts, with optimization tips. Needs Node.js.

Designs and builds MCP servers: first picks a deployment model among remote HTTP, MCPB bundles and local stdio, then guides tool design, auth and in-chat interactive components. Maintained by Anthropic.

Creates or improves Agent Skills from scratch: writes eval cases to test them, runs benchmarks with variance analysis, and tunes descriptions for more accurate triggering. Maintained by Anthropic.

Lightweight multi-protocol command-line downloader that fetches in parallel segments from multiple sources over HTTP(S), FTP, SFTP, BitTorrent and Metalink. Resumes downloads, reads URLs in bulk from text files and offers a JSON-RPC interface for scripts or agents.

Official skill for OpenMAIC, Tsinghua THU-MAIC's open-source multi-agent classroom: from a topic or PDF it generates a full lesson with slides, quizzes, interactive simulations, project-based learning and AI teacher narration. Use a hosted access code, or self-host with an LLM API key.

Color rules for daisyUI 5: explains semantic names such as primary, base-100 and error with their -content foregrounds, says to prefer them over fixed Tailwind colors and never add dark: to them, and shows how to enable, create and override themes. Part of the official daisyUI skill.

Plugin for building LLM apps: LangGraph agents with memory and tool use, hybrid-search RAG, vector index tuning, prompt optimization and LLM evaluation. Includes 3 subagents and 8 skills.

MLOps plugin from the wshobson/agents marketplace: data scientist, ML engineer and MLOps engineer subagents and a /ml-pipeline command that runs the pipeline in phases from data analysis and training to deployment and monitoring, plus ML pipeline and recommender system skills.

Data engineering plugin from the wshobson/agents marketplace: a data engineer subagent, a data pipeline command, and skills for Airflow DAGs, dbt transformations, Spark tuning and data quality, to help build ETL and data warehouses.

Engine for math and explainer animations in Python (Community Edition, ManimCE): write scenes and render them to video with the manim command, letting agents create teaching and science animations. On macOS install cairo and pkg-config first; formulas need LaTeX.

UI/UX design plugin from the wshobson/agents marketplace with 3 subagents, 9 skills and commands for design review, component creation and accessibility audits, covering design tokens, WCAG 2.2, responsive layout, iOS HIG and Material Design 3 for in-code UI design and review.

Quant trading plugin from the wshobson/agents marketplace: quant analyst and risk manager subagents plus backtesting and risk metrics skills for strategy backtests, portfolio optimization and risk measures like VaR, Sharpe ratio and max drawdown. Needs local Python; not investment advice.

Accessibility review plugin with an audit command, a UI validation subagent, and WCAG 2.2 and screen reader testing skills. Before design reviews or launch, the agent checks contrast, keyboard use and screen reader support and suggests fixes. For Claude Code; automated checks need Node.js.

Headless browser written from scratch in Zig for AI agents and automation, using less memory and running faster than headless Chrome in official benchmarks. fetch turns pages into Markdown, and it can serve CDP or MCP. Telemetry is on by default (an env var disables it); Windows needs WSL.

MCP built into the open-source social media scheduler Postiz: agents draft, schedule and publish posts and view analytics across 30+ platforms including X, LinkedIn, Instagram and YouTube. The cloud version uses browser OAuth, no API key (paid after a 7-day trial); self-hosting is free.

Cross-platform shell built around structured data: pipelines pass tables instead of plain text, and you can open and query JSON, CSV, TOML and more directly. Default builds include nu --mcp, which serves it to agents as an MCP server.

Converts PDFs, images, PPTX, DOCX, XLSX, EPUB and more into Markdown, JSON or HTML, preserving tables, formulas and layout, with optional LLM help for higher accuracy. Needs Python 3.10+ and PyTorch; large-scale commercial use of the model weights needs a paid license.

Browser automation MCP server open-sourced by ByteDance in the UI-TARS-desktop repo: drives pages through Puppeteer accessibility data with an optional vision mode, running locally over stdio or remotely over SSE or Streamable HTTP.

ByteDance's open-source multimodal agent CLI: operates browsers via vision or the DOM and calls terminal, file and MCP tools to complete tasks, with a Web UI and headless server mode. Needs Node.js 22+ and a model API key.

When a user asks whether a skill exists for some task, searches the skills.sh ecosystem with the skills CLI, then recommends and installs a fit. Maintained by Vercel Labs and shipped in the skills CLI repo.

Package manager for the open Agent Skills ecosystem: one command installs skills from GitHub and other sources into Claude Code, Codex, Cursor and dozens more agents, with search, update and removal. From Vercel Labs.

Detects your CPU, memory and GPU and scores open models on whether they run, speed, quality and context, then works with local runtimes like Ollama, llama.cpp and MLX to download and benchmark them. recommend --json gives agent-friendly output.

Trading research agent from HKU's HKUDS whose MCP server offers 70+ tools for quotes, financials, backtesting and research across A-shares, Hong Kong and US stocks and crypto. Needs local Python; HK, US and crypto research need no API key. For research only; not investment advice.