Confidential guide on numerology and astrology, based of GG33 Public information

Flujo
MCP-Hub et -inspecteur, flux de travail multi-modélic et interface de chat
3 years
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DISCLAIMER
====> FLUJO is still an early preview! Expect it to break at some points, but improve rapidly! <====
For anything that you struggle with (MCP Installation, Application Issues, Usability Issues, Feedback): PLEASE LET ME KNOW! -> Create a Github Issue or write on Discord (https://discord.gg/KPyrjTSSat) and I will look into it! Maybe a response will take a day, but I will try to get back to each and every one of you.
Here's a video guiding you through the whole thing - from installation to output! (15min) Sorry for the bad audio, a new Video is coming soon!
IMPORTANT SECURITY NOTE
FLUJO has currently EXTENSIVE logging enabled by default! This may expose your encrypted API-Keys to the terminal output!. Be VERY careful when grabbing videos or streaming and showing the terminal output!
FLUJO
FLUJO is an open-source platform that bridges the gap between workflow orchestration, Model-Context-Protocol (MCP), and AI tool integration. It provides a unified interface for managing AI models, MCP servers, and complex workflows - all locally and open-source.
FLUJO is powered by the PocketFlowFramework and built with CLine and a lot of LOVE.
🌟 Key Features
🔑 Environment & API Key Management
- Secure Storage: Store environment variables and API keys with encryption
- Global Access: Use your stored keys across the entire application
- Centralized Management: Keep all your credentials in one secure place
🤖 Model Management
- Multiple Models: Configure and use different AI models simultaneously
- Pre-defined Prompts: Create custom system instructions for each model
- Provider Flexibility: Connect to various API providers (OpenAI, Anthropic, etc.)
- Local Models: Integrate with Ollama for local model execution
🔌 MCP Server Integration
- Easy Installation: Install MCP servers from GitHub or local filesystem
- Server Management: Comprehensive interface for managing MCP servers
- Tool Inspection: View and manage available tools from MCP servers
- Environment Binding: Connect server environment variables to global storage
- Docker Support: Run Docker-based MCP servers within Flujo
🔄 Workflow Orchestration
- Visual Flow Builder: Create and design complex workflows
- Model Integration: Connect different models in your workflow
- Tool Management: Allow or restrict specific tools for each model
-
Prompt Design: Configure system prompts at multiple levels (Model, Flow, Node)
💬 Chat Interface
- Flow Interaction: Interact with your flows through a chat interface
- Message Management: Edit or disable messages or split conversations to reduce context size
- File Attachments: Attach documents or audio for LLM processing (really bad atm, because for this you should use mcp!)
- Transcription: Process audio inputs with automatic transcription (really bad atm, see roadmap)
🔄 External Tool Integration
- OpenAI Compatible Endpoint: Integrate with tools like CLine or Roo
- Seamless Connection: Use FLUJO as a backend for other AI applications
🚀 Getting Started
Manual installation:
Prerequisites
- Node.js (v18 or higher)
- npm or yarn
Installation
-
Clone the repository:
git clone https://github.com/mario-andreschak/FLUJO.git cd FLUJO
-
Install dependencies:
npm install # or yarn install
-
Start the development server:
npm run dev # or yarn dev
-
Open your browser and navigate to:
http://localhost:4200
-
FLUJO feels and works best if you run it compiled:
npm run build npm start
-
To run as a desktop application:
npm run electron-dev # Development mode # or npm run electron-dist # Build and package for your platform
📖 Usage
Setting up often used API keys
- Navigate to Settings
- Save your API Keys globally to secure them
Setting Up Models
- Navigate to the Models page
- Click "Add Model" to create a new model configuration
- Configure your model with name, provider, API key, and system prompt
- Save your configuration
Managing MCP Servers
- Go to the MCP page
- Click "Add Server" to install a new MCP server
- Choose from GitHub repository or local filesystem
- Configure server settings and environment variables
- Start and manage your server
Using official Reference servers
- Go to the MCP page
- Click "Add Server" to install a new MCP server
- Go to the "Reference Servers" Tab
- (First time executing:) Click "Refresh" and waaaaaaait.
- Click a server of your choice, wait for the screen to change, click "Save" / "Update Server" at the bottom.
Using Docker-based MCP Servers
When running FLUJO in Docker, you can use Docker-based MCP servers:
- Go to the MCP page
- Click "Add Server" to install a new MCP server
- Choose "Docker" as the installation method
- Provide the Docker image name and any required environment variables
- Start and manage your server
Creating Workflows
- Visit the Flows page
- Click "Create Flow" to start a new workflow
- Add processing nodes and connect them
- Configure each node with models and tools
- Save your flow
Branching
- Connect one MCP node to multiple subsequent ones
- Define the branching in the prompt, using the handoff-tools on the "Agent Tools" tab
Loops
- Same as branching, but connect back to a previous node
Orchestration
- Same as loops but with multiple ones
Using the Chat Interface
- Go to the Chat page
- Select a flow to interact with
- Start chatting with your configured workflow
🔄 MCP Integration
FLUJO provides comprehensive support for the Model Context Protocol (MCP), allowing you to:
- Install and manage MCP servers
- Inspect server tools
- Connect MCP servers to your workflows
- Reference tools directly in prompts
- Bind environment variables to your global encrypted storage
Docker Installation
The easiest way to run FLUJO is using Docker, which provides a consistent environment and supports running Docker-based MCP servers.
Prerequisites
- Docker and Docker Compose installed on your system
Using Docker Compose
-
Clone the repository:
git clone https://github.com/mario-andreschak/FLUJO.git cd FLUJO
-
Build and start the container:
docker-compose up -d
-
Access FLUJO in your browser:
http://localhost:4200
Using Docker Scripts
For more control over the Docker build and run process, you can use the provided scripts:
-
Build the Docker image:
./scripts/build-docker.sh
-
Run the Docker container:
./scripts/run-docker.sh
Options for run-docker.sh:
-
--tag=<tag>
: Specify the image tag (default: latest) -
--detached
: Run in detached mode -
--no-privileged
: Run without privileged mode (not recommended) -
--port=<port>
: Specify the host port (default: 4200)
For more detailed information about Docker support, including Docker-in-Docker capabilities, persistent storage, and troubleshooting, see DOCKER.md.
📄 License
FLUJO is licensed under the MIT License.
🚀 Roadmap
Here's a roadmap of upcoming features and improvements:
- Real-time Voice Feature: Adding support for Whisper.js or OpenWhisper to enable real-time voice capabilities.
- Visual Debugger: Introducing a visual tool to help debug and troubleshoot more effectively.
- MCP Roots Support: Implementing Checkpoints and Restore features within MCP Roots for better control and recovery options.
- MCP Prompts: Enabling users to build custom prompts that fully leverage the capabilities of the MCP server.
- MCP Proxying STDIO<>SSE: Likely utilizing SuperGateway to proxy standard input/output with Server-Sent Events for enhanced communication: Use MCP Servers managed in FLUJo in any other MCP client.
- Enhanced Integrations: Improving compatibility and functionality with tools like Windsurf, Cursor, and Cline.
- Advanced Orchestration: Adding agent-driven orchestration, batch processing, and incorporating features inspired by Pocketflow.
- Online Template Repository: Creating a platform for sharing models, flows, or complete "packages," making it easy to distribute FLUJO flows to others.
- Edge Device Optimization: Enhancing performance and usability for edge devices.
🤝 Contributing
Contributions are welcome! Feel free to open issues or submit pull requests.
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature
) - Commit your changes (
git commit -m 'Add some amazing feature'
) - Push to the branch (
git push origin feature/amazing-feature
) - Open a Pull Request
📬 Contact
- GitHub: mario-andreschak
- LinkedIn: https://www.linkedin.com/in/mario-andreschak-674033299/
Notes:
- You can add ~FLUJO=HTML, ~FLUJO=MARKDOWN, ~FLUJO=JSON, ~FLUJO=TEXT in your message to format the response, this will give varying results in different tools where you integrate FLUJO.
- You can add ~FLUJOEXPAND=1 or ~FLUJODEBUG=1 somewhere in your message to show more details
- in config/features.ts you can change the Logging-level for the whole application
- in config/features.ts you can enable SSE support which is currently disabled by default
FLUJO - Empowering your AI workflows with open-source orchestration.
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Reviews

user_N6iD1JMH
FLUJO is an amazing tool created by mario-andreschak, available on GitHub. As a dedicated MCP application user, I find FLUJO to be exceptionally user-friendly and efficient in managing workflows. It truly enhances productivity and streamlines processes. I highly recommend checking it out at https://github.com/mario-andreschak/FLUJO for anyone looking to improve their workflow management.