Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者提供的说明(英文原文)
MCP server + Claude Code plugin for ComfyUI: run workflows, generate images, manage models & VRAM.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"comfyui": {
"command": "npx",
"args": [
"-y",
"comfyui-mcp"
]
}
}
}在终端中运行这条命令
claude mcp add comfyui -- npx -y comfyui-mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"comfyui": {
"command": "npx",
"args": [
"-y",
"comfyui-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"comfyui": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"comfyui-mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月8日
注册名称已通过 GitHub 账户 artokun 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.52.206)于25天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Figma Context MCP, Claude Real Video, Figma MCP Server
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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
只显示了开头部分;其余内容请在仓库中阅读