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  1. Home
  2. 🎥 Multimedia Process
  3. Comfyui MCP Server
Comfyui MCP Server logo
Health: ActiveRecent health check succeeded.Last checked 9/22/2026, 8:02:42 PM

Comfyui MCP Server

User RatingsBe the first to rate and review this MCP server! Enrichment pendingWe haven’t run our AI enrichment pass on this listing yet, so the overview, use cases, and FAQ below may be sparse or missing. We work through the catalog over time — check back soon.
View Repository9 GitHub StarsTotal stargazers on GitHub for the source repository (9 stars).Visit Website

MCP Server that transforms ComfyUI workflows into AI-callable tools for MCP Host

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Remote HTTP
Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "comfyui-mcp-server": {
      "url": "http://127.0.0.1:8189/mcp"
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives🎥 More in Multimedia Process

Documentation Overview

ComfyUI-MCP-Server - ComfyUI Model Context Protocol Integration

[简体中文] [ENGLISH]

License: MIT Node.js MCP Protocol Github Ask DeepWiki GitHub stars GitHub forks

[!NOTE] ⭐ 如果您喜欢该项目或觉得有帮助,请给项目点一个 Star,您的支持是我们持续改进的动力!

ComfyUI-MCP-Server 是一个基于 MCP(Model Context Protocol / 模型上下文协议)的服务器实现,将 ComfyUI 中用户定义的工作流转化为参数可配置的 MCP 工具,供 AI 代理(Agents)直接使用。

本项目提供 Python 与 TypeScript 两个独立语言版本,功能基本对等,可按需选用:

Python Version Typescript Version

注:Python 版本带有更多实验性功能,TypeScript 版本则更稳定。

📋 项目功能

通过本项目,您可以通过连接ComfyUI从而赋予 AI 助手(如 Claude Desktop、Trae、Dify 等)强大的多媒体生成能力:

能力说明
图像/视频生成通过使用用户自定义工作流,驱动 AI 助手生成图像、视频等多媒体文件;支持 AI 修改由用户公布的节点参数以微调结果。
自定义工作流导入可手动将 ComfyUI API 格式的 JSON 文件导入服务器工作流目录,自动完成校验与挂载后即刻可用。
生成资产管理生成完成后,自动将多媒体文件下载并保存至本地指定目录。
高级自定义执行支持由 AI 自行提供完整 API JSON 直接调度 ComfyUI(高级模式)。
素材导入支持从本地路径或 HTTP URL 将图片/视频素材上传至 ComfyUI 输入目录,供工作流直接调用。

✨ 项目特色

  • 🔌 工作流即工具:将 ComfyUI 的节点图抽象为可供Agent使用的工具。
  • 🎛️ 自定义参数暴露:可在工作流中精确定义哪些参数对外可见,限定 AI 在暴露范围内操作,防止模型幻觉与误操作。
  • 🔧 零侵入接入:无需修改 ComfyUI 本体或安装任何必要插件,部署即连,开箱即用。
  • 📥 自定义工作流导入:可手动导入 API 格式的工作流 JSON 文件,通过校验后即刻对 Agent 可用,无需重启服务。
  • 📂 资产管理:支持从本地路径或网络 URL 自动上传资源至 ComfyUI。
  • ⚡ 流式与进度支持:支持生成进度报告(需 Client/Host 支持)。
  • 🌍 国际化双语支持:内置中英文(zh-CN/en)国际化。
  • 🧩 标准 MCP 适配:全面支持 STDIO 与 Streamable HTTP 通信协议。
  • 🔬 Skills 支持:包含项目技能手册SKILL.md,针对支持 Skills 的 AI 助手通过 Skills 进行深度优化。

更多详情可查阅 为什么选择我们

🧰 可用工具集

AI 代理可以通过 MCP 协议调用以下内置工具:

工具工具名称描述
get_core_manual获取项目核心手册【系统指引】核心协议与操作字典。初始化或调用其他工具前必须优先读取,获取最新参数填充策略与报错恢复机制。
get_workflows_catalog获取工作流目录【目录检索】获取当前服务器支持的所有工作流清单。涉及生图的指令必须精确匹配此清单,严禁伪造或猜测工作流名称。
get_workflow_API获取工作流详情【工作流API】读取目标工作流的全量底层拓扑JSON。体积庞大,仅在执行异常需排查最底层逻辑时调用,严禁在常规业务中使用防污染上下文。
mount_workflow挂载工作流【参数挂载】提取目标生成任务的受支持交互参数Schema(屏蔽连线细节)。提交工作流任务前,必须调用此接口获取合法的参数键名表。
queue_prompt执行工作流任务【任务提交】向队列提交任务 Prompt。底层自动调度计算节点并向 Host 实时同步进度。必须确保所有键名已通过挂载校验,严禁编造键名。
queue_custom_prompt执行自定义工作流【高级模式】直接向队列提交完整的原生 ComfyUI API Prompt JSON。仅在调试底层方案或响应明确专家指令时开放,常规任务严禁使用。
save_custom_workflow保存自定义工作流【保存工作流】将自定义参数化工作流保存到服务器的工作流目录中并随后自动执行语法校验和挂载。提交的 JSON 必须符合规范(至少包含一处符合挂载规则的 ==名称== 节点),否则将被拒绝保存。
save_task_assets保存生成资产【保存生成资产】获取指定任务 (prompt_id) 的执行历史,并将产生的所有多媒体生成物 (图片、视频、GIF等) 下载并保存到指定的本地目录中。
interrupt_prompt取消任务【任务取消】取消特定 prompt_id 的运算进程并强制移除队列中的等待项。
get_prompt_result获取任务结果【输出快照与资产】获取特定 Prompt 执行完成后的节点快照,提取生成的目标媒体文件(图像/视频链接)或回溯 Traceback 诊断错误。
get_system_status获取系统状态【系统监控】采集内存、显存及 Python 运行时指标,用于排查 OOM 或服务死锁等底层异常。
list_models检索模型文件【模型目录】轮询本地磁盘模型存放区。参数涉及具体模型文件时,必须前置调用此接口枚举校准,严禁凭空伪造模型文件名。
upload_assetsComfyUI导入资产【上传文件】将本地文件或网络 URL 上传至 ComfyUI 服务器的 input 目录,以便在工作流中直接应用。

🏆 为什么选择我们?

特性ComfyUI MCP Server其他类似项目
自定义参数暴露✅ 支持❌ 有限支持或不支持
无需修改 ComfyUI✅ 完全支持❌ 通常需要修改或插件
自然语言交互✅ 支持❌ 通常需要 API 调用
实时进度通知✅ 支持❌ 有限支持
多传输方式✅ STDIO + HTTP❌ 通常仅支持一种
国际化支持✅ 内置❌ 通常仅支持英文
会话管理✅ 完善❌ 基本或无

更多详情可查阅 为什么选择我们

🎬 演示视频

默认方式

点击下方图片观看演示视频。

API_JSON 方式

点击下方图片观看演示视频。

🚀 快速开始

仅需两步,快速启动项目。

提醒:安装启动项目后,还需查阅[使用教程],否则无法使用工作流相关功能。

准备工作(必需)

在启动本项目之前,请确保您的系统中已安装以下软件

  • Node.js 18+ [官方链接]
  • ComfyUI 0.9.1+ [官方链接]
  • MCP 客户端/AI Agent,例如Claude Desktop、Cursor等

第一步:安装项目与依赖

1. 克隆本项目 在终端中执行以下命令:

bash
git clone https://github.com/MetaBrain-Labs/ComfyUI-MCP-Server-TypeScript.git

2. 移动到项目目录

bash
cd ComfyUI-MCP-Server-TypeScript

3. 安装依赖

Terminal
npm install

第二步:配置环境与启动项目

1. 项目环境配置

进入项目根目录,根据系统实际情况修改 .env 文件中的配置。 详细配置说明请查阅:[环境变量]

2. 连接并运行项目

根据您的需求选择传输方式以启动项目:

[!TIP] MCP传输机制

MCP 协议目前定义了两种客户端-服务器通信的标准传输机制:

  • STDIO
  • Streamable HTTP

本项目两者皆支持,请根据您的 MCP 客户端能力进行选择。

您有责任确保使用这些服务器符合相关条款,以及适用于您的任何法律、规则、法规、政策或标准。

模式一:STDIO 连接 (推荐用于 Claude Desktop 等本地客户端)

  • MCP客户端启动: 复制下述 JSON 文件,在 MCP 客户端的 MCP 配置中粘贴并修改即可。

    [!NOTE]

    部分 MCP 客户端配置 MCP Server 的方法请查阅:[示例]

    其他项目设置请在环境变量中修改,参数详情请查阅:[环境变量]

    如果 ComfyUI 在云端运行,请将 "SYNC_MODE" 设置为 "manual"

    config.json
    {
      "mcpServers": {
        "comfy-ui-advanced": {
          "command": "npx",
          "args": [
            "tsx",
            "<项目根目录绝对路径,如 D:/ComfyUI-MCP-Server-TypeScript>"
          ],
          "env": {
            "LOCALE": "en",
            "MCP_SERVER_URL": "http://127.0.0.1:8189/mcp",
            "MCP_SERVER_IP": "127.0.0.1",
            "MCP_SERVER_PORT": "8189",
            "COMFY_UI_SERVER_IP": "http://127.0.0.1:8188",
            "COMFY_UI_SERVER_HOST": "127.0.0.1",
            "COMFY_UI_SERVER_PORT": "8188",
            "SYNC_MODE": "timed",
            "SYNC_POLL_INTERVAL_SECONDS": "3",
            "SYNC_EVENT_FALLBACK_INTERVAL_SECONDS": "300",
            "ONDEMAND_REFRESH_COOLDOWN_SECONDS": "3",
            "COMFY_UI_INSTALL_PATH": "",
            "WORKFLOW_NAME_REGEX": "^==(.+?)==$",
            "WORKFLOW_PARAM_REGEX": "^=>(.+)$",
            "LOG_LEVEL": "INFO"
          }
        }
      }
    }
    
  • 终端启动:
    bash
    # 终端连接启动方式无需配置json,直接在项目根目录下执行:
    npm run dev
    

模式二:StreamHTTP 连接 (推荐用于网络化/分布式部署)

  • MCP客户端启动: StreamHTTP 的项目设置在 [.env] 中指定,无需在下述 JSON 中配置。

    [!NOTE]

    部分 MCP 客户端配置 MCP Server 的方法请查阅:[示例]

    目前支持 StreamHTTP 的 MCP Client/Host 较少,请根据需求使用。

    如果 ComfyUI 在云端运行,请在 [.env] 中将 "SYNC_MODE" 设置为 "manual"

    config.json
    {
      "mcpServers": {
        "comfy-ui-advanced-http": {
          "url": "http://127.0.0.1:8189/mcp"
        }
      }
    }
    
  • 终端启动:
    bash
    # 启动 Streamable HTTP
    npm run dev
    

至此,项目部署且启动完成。若您需要调试工具,请继续阅读下文,否则请直接跳转至[使用教程]。

调试工具 (MCP Inspector)

Inspector是MCP官方提供的MCP调试工具,推荐使用StreamHTTP作为Inspector的连接方式。

  • 克隆项目
  • 安装相关依赖
    Terminal
    npm install
    
  • 启动StreamHTTP连接方式的Server:
    bash
    # 1. 在终端 A 启动 HTTP 服务
    npm run dev
    
  • 启动Inspector:
    bash
    # 2. 在终端 B 启动 Inspector
    npm run inspector
    

启动完成后,控制台中会出现类似下述地址,复制地址到浏览器后即可开始调试相关工具:

bash
# 每次启动MCP_PROXY_AUTH_TOKEN都不一样,因此每次启动后需要及时切换链接
http://localhost:6274/?MCP_PROXY_AUTH_TOKEN=d66fcf6cbbb3723c60bfef51f020e5e96811002a675e7162b065b44f2fe377f3

inspector启动成功后,浏览器页面配置参考:

inspector配置示例

📖 使用教程

本项目需要对 ComfyUI 工作流进行简单的特定标记,以使 AI Agent 能够准确识别和调用,可以通过以下两种方式添加可用工作流:

标记规则(必须了解)

无论使用哪种方式添加可用工作流,都必须在其工作流中添加以下标记节点:

Read the full README →View source on GitHub →

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Last commit
6mo ago
Most recent push to the default branch.
Directory activity
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Frequently Asked Questions about Comfyui MCP Server

comfyui-mcp-server is a hosted MCP server. Add it as a remote server in your client's config: "mcpServers": { "comfyui-mcp-server": { "url": "http://127.0.0.1:8189/mcp" } }

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Technical Specs & Signals

Category🎥Multimedia Process
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TransportSSE (Remote)
Last updatedMar 20, 2026
10/15 checks healthy over the last 45d
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GitHub stars9
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Last commit6mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Mar 20, 2026
36Quality signal: Fair · 36/100How this signal is calculated ▾
Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools15/30
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Scanned 8/18/2026 via OSV.dev · http://127.0.0.1:8189/mcp (npm)

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