AIDC-AI/Pixelle-MCP

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✨ An AIGC solution based on the MCP protocol, supporting both local ComfyUI and cloud ComfyUI (RunningHub) modes, seamlessly converting workflows into MCP tools with zero code.
https://github.com/user-attachments/assets/65422cef-96f9-44fe-a82b-6a124674c417
📋 Recent Updates
- ✅ **2025-09-29**: Added RunningHub cloud ComfyUI support, enabling workflow execution without local GPU and ComfyUI environment
- ✅ **2025-09-03**: Architecture refactoring from three services to unified application; added CLI tool support; published to PyPI
- ✅ **2025-08-12**: Integrated the LiteLLM framework, adding multi-model support for Gemini, DeepSeek, Claude, Qwen, and more
🚀 Features
- ✅ 🔄 **Full-modal Support**: Supports TISV (Text, Image, Sound/Speech, Video) full-modal conversion and generation
- ✅ 🚀 **Dual Execution Modes**: Local ComfyUI self-hosted environment + RunningHub cloud ComfyUI service, users can flexibly choose based on their needs
- ✅ 🧩 **ComfyUI Ecosystem**: Built on ComfyUI, inheriting all capabilities from the open ComfyUI ecosystem
- ✅ 🔧 **Zero-code Development**: Defines and implements the Workflow-as-MCP Tool solution, enabling zero-code development and dynamic addition of new MCP Tools
- ✅ 🗄️ **MCP Server**: Based on the MCP protocol, supporting integration with any MCP client (including but not limited to Cursor, Claude Desktop, etc.)
- ✅ 🌐 **Web Interface**: Developed based on the Chainlit framework, inheriting Chainlit's UI controls and supporting integration with more MCP Servers
- ✅ 📦 **One-click Deployment**: Supports PyPI installation, CLI commands, Docker and other deployment methods, ready to use out of the box
- ✅ ⚙️ **Simplified Configuration**: Uses environment variable configuration scheme, simple and intuitive configuration
- ✅ 🤖 **Multi-LLM Support**: Supports multiple mainstream LLMs, including OpenAI, Ollama, Gemini, DeepSeek, Claude, Qwen, and more
📁 Project Architecture
Pixelle MCP adopts a **unified architecture design**, integrating MCP server, web interface, and file services into one application, providing:
- 🌐 **Web Interface**: Chainlit-based chat interface supporting multimodal interaction
- 🔌 **MCP Endpoint**: For external MCP clients (such as Cursor, Claude Desktop) to connect
- 📁 **File Service**: Handles file upload, download, and storage
- 🛠️ **Workflow Engine**: Supports both local ComfyUI and cloud ComfyUI (RunningHub) workflows, automatically converts workflows into MCP tools
🏃‍♂️ Quick Start
Choose the deployment method that best suits your needs, from simple to complex:
🎯 Method 1: One-click Experience
> 💡 **Zero configuration startup, perfect for quick experience and testing**
🚀 Temporary Run
📚 **View uvx CLI Reference →**
📦 Persistent Installation
📚 **View pip CLI Reference →**
After startup, it will automatically enter the **configuration wizard** to guide you through execution engine selection (ComfyUI/RunningHub) and LLM configuration.
🛠️ Method 2: Local Development Deployment
> 💡 **Supports custom workflows and secondary development**
📥 1. Get Source Code
🚀 2. Start Service
📚 **View Complete CLI Reference →**
🔧 3. Add Custom Workflows (Optional)
**⚠️ Important**: Make sure to test workflows in ComfyUI first to ensure they run properly, otherwise execution will fail.
🐳 Method 3: Docker Deployment
> 💡 **Suitable for production environments and containerized deployment**
📋 1. Prepare Configuration
🚀 2. Start Container
🌐 Access Services
Regardless of which method you use, after startup you can access via:
- **🌐 Web Interface**: http://localhost:9004
*Default username and password are both dev, can be modified after startup*
- **🔌 MCP Endpoint**: http://localhost:9004/pixelle/mcp
*For MCP clients like Cursor, Claude Desktop to connect*
**💡 Port Configuration**: Default port is 9004, can be customized via environment variable PORT=your_port.