Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
제작자가 쓴 설명(영어 원문)
MCP server + Claude Code plugin for ComfyUI: run workflows, generate images, manage models & VRAM.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"comfyui": {
"command": "npx",
"args": [
"-y",
"comfyui-mcp"
]
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add comfyui -- npx -y comfyui-mcp프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"comfyui": {
"command": "npx",
"args": [
"-y",
"comfyui-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"comfyui": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"comfyui-mcp"
]
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 artokun 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
레지스트리에 필수 키가 나와 있지 않아요. 다만 처음 쓸 때 로그인을 요구하는 서버도 있어요.
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.52.206)은 24일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Node.js도 있어야 해요.
같은 카테고리에는: Figma Context MCP, Claude Real Video, Figma MCP Server
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
The Figma MCP server brings Figma design context directly into your AI workflow.
제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
The Agent panel driving ComfyUI end to end. It reads what is installed locally, wires the graph, frees VRAM, and runs the render.
Watch the 76s demo →
The local-first, agent-native control plane for [ComfyUI](https://github.com/comfyanonymous/ComfyUI). An MCP server plus a live sidebar agent that generates images, video and audio, authors and runs workflows, manages models and custom nodes, and edits your live ComfyUI graph in natural language. Bring whatever model you have: Claude or ChatGPT on your subscription, Gemini on your Google login, a free local model via Ollama (fully offline), or any hosted model over one API key (DeepSeek, GLM, MiMo, Kimi, GPT, Claude via OpenRouter). The tools and the panel are the same on every tier, and the built-in LLM Arena scores each model on real ComfyUI tasks so you know what yours can do. One config targets local installs, LAN, VPS, or Comfy Cloud.
One-click GPU pod. A ready-to-run ComfyUI with this project + Agent Panel + ComfyUI-Manager v2 preinstalled, on your own GPU. No setup.
Works on macOS, Linux, and Windows. Auto-detects your ComfyUI installation and port.
Stuck or have a question? [Join the Discord](https://discord.gg/cW9arBhzCu) for help, model tips, and release announcements.
38 MCP tools | 42 AI skills (Flux · WAN · LTX 2.3 video · MiniMax H3 · Qwen · Z-Image · Ideogram 4 · ERNIE · ANIMA · model registry · Civitai · node authoring · launch/perf flags) | 56 installer packs | 11 slash commands | 4 autonomous agents | 3 hooks
The plugin ships skills that grow with every release: model-specific generation guides with curated download URLs, workflow recipes, troubleshooting, and custom-node authoring. With them, Claude knows the right sampler, CFG, resolution, and model files for each architecture without trial and error.
### Now available: the ComfyUI Agent Panel on ComfyUI-Manager & the Comfy Registry
An autonomous AI agent in your ComfyUI sidebar, running on Claude, ChatGPT, Gemini, or ANY local/hosted LLM (Ollama and every OpenAI-compatible endpoint). Subscriptions work with no API key; local models work with no account at all. Pick a provider and it drives your live graph: edits, spatial layout, one-shot workflow/pack loads, rewind/rollback, a pending-message tray, activity cards, multi-tab. It asks before spending paid API credits.
Search
comfyui-agent-panelin ComfyUI-Manager to install. Read more →
Full documentation: [comfyui-mcp.artokun.io/docs](https://comfyui-mcp.artokun.io/docs)
1. Install ComfyUI (if you haven't already): ComfyUI Desktop or from source
2. Add the MCP server to your Claude Code config (~/.claude/settings.json):
{
"mcpServers": { "comfyui": { "command": "npx", "args": ["-y", "comfyui-mcp"], "env": { "CIVITAI_API_TOKEN": "" } } } }
3. Start using it. With ComfyUI running, ask Claude to generate an image:
> Generate an image of a sunset over mountains
Claude will find (or download) a checkpoint, build a workflow, execute it, and return the image.
Note: This runs as a standalone MCP server, so there is no need to clone this repo.
npxdownloads and runs it.
comfyui-mcp is local-first. A self-hosted ComfyUI on Mac/Linux/Windows is the primary target, and the same agent reaches remote installs (RunPod, VPS, LAN, reverse-proxied) from one config. Local-first, not local-only.
More than a bridge. Most ComfyUI MCP servers are thin connectors. They forward a prompt and hand back an image. comfyui-mcp is a full control plane. It authors and edits the graph node by node, runs and iterates on workflows, manages models and custom nodes, and ships model-specific expertise (samplers, CFG, resolutions, curated model URLs) so the agent gets it right without trial and error. If you want a minimal local relay, a lightweight server is fine. If you want an agent that *operates* ComfyUI, that's this project.
For Comfy Cloud users, Comfy-Org ships its own agent tooling: Comfy Cloud MCP (public beta, hosted on Comfy Cloud GPUs), the Comfy In-App Agent (private alpha, inside Comfy Cloud), and a first-party Comfy Local MCP (private test, not publicly available yet), all maintained by the Comfy team. If you don't have a GPU or you want zero setup, that's the better path; go use it.
Where this project differs is that it runs on your install and your choice of model, including a free local one via Ollama with no account and no network at all. comfyui-mcp *also* includes a community cloud mode (set COMFYUI_API_KEY, see Deployment modes) so a single MCP can target all three deployment shapes from one config.
[Local vs. Comfy Cloud agent](https://comfyui-mcp.artokun.io/docs/local-vs-comfy-cloud) is a side-by-side comparison, including when Comfy Cloud is the right answer. *(Statuses above are as of July 2026. Comfy-Org ships fast, so check their docs for the current state.)*
To use comfyui-mcp from Claude Desktop's Custom Connectors or any remote client, like Comfy's own cloud.comfy.org/mcp connector, run it as an authenticated, publicly reachable Streamable-HTTP server with one flag:
npx -y comfyui-mcp@latest --tunnel
This forces the HTTP transport, generates an auth token, opens a cloudflared quick tunnel, and prints a ready-to-paste https://…/mcp URL + token + Claude Desktop connector snippet. Auth accepts Authorization: Bearer or X-API-Key: (matching Comfy Cloud's convention). See the Remote / hosted connector guide for the full walkthrough and headless usage.
Auth is opt-in. With no
COMFYUI_MCP_HTTP_TOKENset and no--tunnel, the
default stdio (and plain
--httpon loopback) behavior is unchanged. It stays open and
local. OAuth (Comfy's browser sign-in flow) is a planned follow-up.
This package also ships as a Claude Code plugin that adds slash commands, skills, agents, and hooks on top of the MCP tools.
# In Claude Code
/plugin marketplace add artokun/comfyui-mcp /plugin install comfy
| Command | Description |
|---|---|
/comfy:gen | Generate an image from a text description — auto-selects checkpoint, builds workflow, returns image |
/comfy:viz | Visualize a workflow as a Mermaid diagram with nodes grouped by category |
/comfy:node-skill | Generate a Claude skill for a custom node pack from Registry ID or GitHub URL |
/comfy:debug [prompt_id] | Diagnose why a workflow failed — reads history, logs, traces root cause, suggests fixes |
/comfy:batch | Parameter sweep generation across cfg, sampler, steps, seed, etc. |
/comfy:convert | Convert between UI format and API format workflows |
/comfy:install | Install a custom node pack — git clone, pip install, optional restart |
/comfy:gallery [filter] | Browse generated outputs with metadata — filter by date, count, or filename |
/comfy:compare | Diff two workflows side by side — shows added/removed nodes and changed parameters |
/comfy:recipe | Multi-step recipes: portrait, hires-fix, style-transfer, product-shot |
42 skills total: model-family guides (Flux, WAN, LTX 2.3, MiniMax H3, Qwen, Z-Image, Ideogram 4, ERNIE, ANIMA + anime / WAN / Z-Image LoRA training), the model-registry (curated download URLs), the civitai pairing skill, node authoring, the launch/performance-flags matrix, and the core four below. Full list on the plugin docs page.
Installer packs.
packs/bundles 13 one-command ComfyUI setups: ANIMA, Ideogram 4, LTX-2.3, ERNIE, WAN (animate / longer-videos / transparent), Qwen (image / image-edit), Z-Image (turbo / base / xy-plot) and artokun-flow (WAN Animate: replace / animate). Each is a manifest of custom nodes + model URLs + workflow that drives bothapply_manifestand generatedinstall-windows.bat/install-runpod.sh, with CI that validates every model link + payload size. Seepacks/README.md.
| Skill | Description |
|---|---|
| comfyui-core | Workflow format, node types, data flow patterns, pipeline architecture, MCP tool usage guide |
| prompt-engineering | CLIP weight syntax (word:1.3), BREAK tokens, embeddings, model-specific prompting for SD1.5/SDXL/Flux/SD3 |
| troubleshooting | Common error catalog — OOM, dtype mismatches, missing nodes, NaN tensors, black images, CUDA errors, with VRAM estimates per model |
| model-compatibility | Compatibility matrix — loaders, resolutions, CFG, samplers, ControlNets, LoRAs, and VAEs per model family (SD1.5/SDXL/Turbo/Lightning/Flux/SD3/LTXV) |
| Agent | Model | Description |
|---|---|---|
| comfy-explorer | Sonnet | Researches custom node packs — reads docs, queries /object_info, generates skill files |
| comfy-debugger | Sonnet | Autonomously diagnoses workflow failures — gathers logs + history, identifies failing node, checks models + custom nodes, proposes and optionally applies fixes |
| comfy-optimizer | Sonnet | Analyzes workflows for performance — detects redundant nodes, VRAM waste, wrong CFG/steps for model family, precision issues, suggests optimizations |
| comfy-researcher | Sonnet | Discovers and ranks ComfyUI custom node packs for a stated image-generation problem |
| Event | Trigger | Action |
|---|---|---|
| PreToolUse | enqueue_workflow | VRAM watchdog — checks GPU memory via /system_stats and warns if < 1GB free before execution |
| PreToolUse | restart_comfyui (actions stop/restart) | Save warning — prompts user to save unsaved workflow changes before stopping ComfyUI |
| PostToolUse | Any comfyui tool | Job completion notify — checks for completed jobs and injects compl
앞부분만 보여 드려요. 나머지는 저장소에서 읽어 보세요