도구

14 skills plus a hook-based reminder layer for use with n8n-mcp: teaches agents to write correct n8n expressions, configure nodes, apply workflow patterns, fix validation errors and deploy self-hosted n8n. Requires n8n-mcp to be set up first.

Lets agents build, run, test and debug iOS and macOS projects and control simulators and physical devices, with a CLI mode too. Formerly XcodeBuildMCP, now maintained by Sentry; macOS only, requires Xcode 16 or later.

ScrapeCreators' official skills: mine public TikTok, Instagram, YouTube, Reddit and X data for viral content, customer voice in comments, competitor accounts and ad libraries, and creator vetting, with sourced reports. Needs a ScrapeCreators key (100 free credits, then pay as you go).

Google's official skills for building ADK agents: dev workflow, scaffolding, the ADK Python API, evaluation with LLM judges and adaptive rubrics, deployment to Agent Runtime, Cloud Run or GKE, publishing and observability. Works with agents-cli; local dev needs only an AI Studio key.

The .NET team's official skill collection, grouped into plugins: ASP.NET Core, Blazor, MAUI, EF Core data access, MSBuild troubleshooting, performance diagnostics, testing, and framework upgrades and migrations. Maintained by Microsoft; install via the Claude Code or Codex plugin marketplace.

Docker's official CLI for building images, running and managing containers, viewing logs and pushing to registries, a foundational tool for agents setting up isolated environments. Needs a local or remote Docker Engine such as Docker Desktop.

Community-maintained MCP for Jira and Confluence: search with JQL/CQL and create or update issues, pages and comments. Supports both Cloud and Server/Data Center deployments; needs an API token or personal access token.

Reference for Vitest 5: config, CLI, the test, describe and expect APIs, hooks, mocking with vi, snapshots, coverage, fixtures, concurrency, filtering and tags, reporters, benchmarks, test environments, type testing and multi-project setups. Generated by Anthony Fu from the official docs.

Full-featured Jira CLI: filter, create, transition, assign and link issues and manage epics and sprints, with --plain text output that agents can read. Works with Cloud and self-hosted Jira; set up an API token and run jira init.

Reference for pnpm 12: CLI, pnpm-workspace.yaml settings, monorepo workspaces, catalogs, overrides, patches, supply-chain settings such as build approval, task orchestration, CI setup and migration from npm, Yarn or older pnpm. Generated by Anthony Fu from the official docs.

Semi-automated research workflow for computer science and AI researchers: ideation, Zotero literature management, experiment analysis and reports, paper writing and polishing, and rebuttals, with optional Obsidian knowledge base. 40+ skills; also installable as a Claude Code plugin.

Semi-automated research assistant for CS and AI researchers that links ideation, Zotero literature management, experiment analysis and reporting, paper writing and reviewer responses, and keeps project knowledge in Obsidian. Branches for Codex and other agents exist.

Automatically cuts silent or static parts from video and audio based on loudness or motion, with adjustable margins and speed changes, and exports project files for Premiere, DaVinci Resolve, Final Cut Pro and other editors. The repo ships an agent skill.

draw.io's official MCP: opens XML, CSV or Mermaid diagrams generated by the agent directly in the draw.io editor, good for flowcharts and architecture diagrams. A no-install remote version can also render diagrams inline in the chat.

Interviews you to design an agentic control loop for your codebase in control-theory terms: a set point, a sensor built from existing tooling, a controller that picks small low-risk changes, and a coding agent that opens PRs. Builds each part to run locally before wiring a scheduled CI workflow.

Turns a repeatable agent task into a repo-local skill plus a GitHub Actions workflow that runs a coding agent (Claude Code, Codex, OpenCode or CodeLayer) on a schedule, with a prompt, memory file and one-open-PR bound. Reads the repo first, then walks you through cadence, scope and validation.

Lossy PNG compression CLI: converts images to 8-bit PNGs that keep transparency, usually 60-80% smaller, with batch processing and a quality range setting. Handy for slimming down web assets, slides and article images. Install via Homebrew on macOS; no account.

High-quality GIF encoder built on pngquant: turns video frames or PNG sequences into animations, using cross-frame palettes and temporal dithering for thousands of colors per frame. Can take video piped straight from ffmpeg.

Community Playwright browser automation MCP from ExecuteAutomation (not Microsoft's official one): navigate, click, fill forms, screenshot and scrape page text, plus send HTTP requests, assert network responses and record actions into test code, with 143 device emulations built in.

GitHub's official gh extension for writing Actions workflows in Markdown that AI agents execute, compiled into standard Actions. Choose engines like Copilot, Claude Code or Codex; runs in a read-only sandbox by default. Requires gh.

Audits and rewrites AI-sounding prose: detects stock phrases using 70+ pattern categories and a tiered replacement word list, with detect-only, rewrite and in-place edit modes and optional voice settings. Rules are calibrated for English.

macOS screen capture, accessibility-tree inspection and native UI automation, served over MCP so agents can see the screen and click, type and operate menus. Requires macOS 15+ with Screen Recording and Accessibility permissions granted.

macOS screenshot and UI automation CLI: capture the screen, read the accessibility tree for structured UI elements, then click, type, and switch windows and menus. Also runs as an MCP server for Claude Code and Codex. Needs macOS 15+ with Screen Recording and Accessibility permissions.

Local FFmpeg video editing skill: ask in plain language to cut and join clips, remove silence, reframe to vertical, add subtitles, normalize loudness and export to TikTok, Reels or YouTube specs, fully offline with no API key. Needs ffmpeg and Python 3; also usable as an MCP.