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BytesAgain β€Ί Skills β€Ί Nodetool
πŸ¦€ ClawHub

Nodetool

by @georgi

Visual AI workflow builder - ComfyUI meets n8n for LLM agents, RAG pipelines, and multimodal data flows. Local-first, open source (AGPL-3.0).

Versionv0.6.3
Downloads3,187
Installs7
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TERMINAL
clawhub install nodetool

πŸ“– About This Skill

name: nodetool description: Visual AI workflow builder - ComfyUI meets n8n for LLM agents, RAG pipelines, and multimodal data flows. Local-first, open source (AGPL-3.0).

NodeTool

Visual AI workflow builder combining ComfyUI's node-based flexibility with n8n's automation power. Build LLM agents, RAG pipelines, and multimodal data flows on your local machine.

Quick Start

# See system info
nodetool info
List workflows

nodetool workflows list
Run a workflow interactively

nodetool run 
Start of chat interface

nodetool chat
Start of web server

nodetool serve

Installation

Linux / macOS

Quick one-line installation:

curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash

With custom directory:

curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash --prefix ~/.nodetool

Non-interactive mode (automatic, no prompts):

Both scripts support silent installation:

# Linux/macOS - use -y
curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash -y
Windows - use -Yes

irm https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.ps1 | iex; .\install.ps1 -Yes

What happens with non-interactive mode:

  • All confirmation prompts are skipped automatically
  • Installation proceeds without requiring user input
  • Perfect for CI/CD pipelines or automated setups

    • Windows

    Quick one-line installation:

    irm https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.ps1 | iex

    With custom directory:

    .\install.ps1 -Prefix "C:\nodetool"

    Non-interactive mode:

    .\install.ps1 -Yes

    Core Commands

    Workflows

    Manage and execute NodeTool workflows:

    # List all workflows (user + example)
nodetool workflows list
    Get details for a specific workflow
    
nodetool workflows get 
    Run workflow by ID
    
nodetool run 
    Run workflow from file
    
nodetool run workflow.json
    Run with JSONL output (for automation)
    
nodetool run  --jsonl

    Run Options

    Execute workflows in different modes:

    # Interactive mode (default) - pretty output
nodetool run workflow_abc123
    JSONL mode - streaming JSON for subprocess use
    
nodetool run workflow_abc123 --jsonl
    Stdin mode - pipe RunJobRequest JSON
    
echo '{"workflow_id":"abc","user_id":"1","auth_token":"token","params":{}}' | nodetool run --stdin --jsonl
    With custom user ID
    
nodetool run workflow_abc123 --user-id "custom_user_id"
    With auth token
    
nodetool run workflow_abc123 --auth-token "my_auth_token"

    Assets

    Manage workflow assets (nodes, models, files):

    # List all assets
nodetool assets list
    Get asset details
    
nodetool assets get

    Packages

    Manage NodeTool packages (export workflows, generate docs):

    # List packages
nodetool package list
    Generate documentation
    
nodetool package docs
    Generate node documentation
    
nodetool package node-docs
    Generate workflow documentation (Jekyll)
    
nodetool package workflow-docs
    Scan directory for nodes and create package
    
nodetool package scan
    Initialize new package project
    
nodetool package init

    Jobs

    Manage background job executions:

    # List jobs for a user
nodetool jobs list
    Get job details
    
nodetool jobs get 
    Get job logs
    
nodetool jobs logs 
    Start background job for workflow
    
nodetool jobs start

    Deployment

    Deploy NodeTool to cloud platforms (RunPod, GCP, Docker):

    # Initialize deployment.yaml
nodetool deploy init
    List deployments
    
nodetool deploy list
    Add new deployment
    
nodetool deploy add
    Apply deployment configuration
    
nodetool deploy apply
    Check deployment status
    
nodetool deploy status 
    View deployment logs
    
nodetool deploy logs 
    Destroy deployment
    
nodetool deploy destroy 
    Manage collections on deployed instance
    
nodetool deploy collections
    Manage database on deployed instance
    
nodetool deploy database
    Manage workflows on deployed instance
    
nodetool deploy workflows
    See what changes will be made
    
nodetool deploy plan

    Model Management

    Discover and manage AI models (HuggingFace, Ollama):

    # List cached HuggingFace models by type
nodetool model list-hf 
    List all HuggingFace cache entries
    
nodetool model list-hf-all
    List supported HF types
    
nodetool model hf-types
    Inspect HuggingFace cache
    
nodetool model hf-cache
    Scan cache for info
    
nodetool admin scan-cache

    Admin

    Maintain model caches and clean up:

    # Calculate total cache size
nodetool admin cache-size
    Delete HuggingFace model from cache
    
nodetool admin delete-hf 
    Download HuggingFace models with progress
    
nodetool admin download-hf 
    Download Ollama models
    
nodetool admin download-ollama

    Chat & Server

    Interactive chat and web interface:

    # Start CLI chat
nodetool chat
    Start chat server (WebSocket + SSE)
    
nodetool chat-server
    Start FastAPI backend server
    
nodetool serve --host 0.0.0.0 --port 8000
    With static assets folder
    
nodetool serve --static-folder ./static --apps-folder ./apps
    Development mode with auto-reload
    
nodetool serve --reload
    Production mode
    
nodetool serve --production

    Proxy

    Start reverse proxy with HTTPS:

    # Start proxy server
nodetool proxy
    Check proxy status
    
nodetool proxy-status
    Validate proxy config
    
nodetool proxy-validate-config
    Run proxy daemon with ACME HTTP + HTTPS
    
nodetool proxy-daemon

    Other Commands

    # View settings and secrets
nodetool settings show
    Generate custom HTML app for workflow
    
nodetool vibecoding
    Run workflow and export as Python DSL
    
nodetool dsl-export
    Export workflow as Gradio app
    
nodetool gradio-export
    Regenerate DSL
    
nodetool codegen
    Manage database migrations
    
nodetool migrations
    Synchronize database with remote
    
nodetool sync

    Use Cases

    Workflow Execution

    Run a NodeTool workflow and get structured output:

    # Run workflow interactively
nodetool run my_workflow_id
    Run and stream JSONL output
    
nodetool run my_workflow_id --jsonl | jq -r '.[] | "\(.status) | \(.output)"'

    Package Creation

    Generate documentation for a custom package:

    # Scan for nodes and create package
nodetool package scan
    Generate complete documentation
    
nodetool package docs

    Deployment

    Deploy a NodeTool instance to the cloud:

    # Initialize deployment config
nodetool deploy init
    Add RunPod deployment
    
nodetool deploy add
    Deploy and start
    
nodetool deploy apply

    Model Management

    Check and manage cached AI models:

    # List all available models
nodetool model list-hf-all
    Inspect cache
    
nodetool model hf-cache

    Installation

    Linux / macOS

    Quick one-line installation:

    curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash

    With custom directory:

    curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash --prefix ~/.nodetool

    Non-interactive mode (automatic, no prompts):

    Both scripts support silent installation:

    # Linux/macOS - use -y
curl -fsSL https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.sh | bash -y
    Windows - use -Yes
    
irm https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.ps1 | iex; .\install.ps1 -Yes

    What happens with non-interactive mode:

  • All confirmation prompts are skipped automatically
  • Installation proceeds without requiring user input
  • Perfect for CI/CD pipelines or automated setups

    • Windows

    Quick one-line installation:

    irm https://raw.githubusercontent.com/nodetool-ai/nodetool/refs/heads/main/install.ps1 | iex

    With custom directory:

    .\install.ps1 -Prefix "C:\nodetool"

    Non-interactive mode:

    .\install.ps1 -Yes

    What Gets Installed

    The installer sets up:

  • micromamba β€” Python package manager (conda replacement)
  • NodeTool environment β€” Conda env at ~/.nodetool/env
  • Python packages β€” nodetool-core, nodetool-base from NodeTool registry
  • Wrapper scripts β€” nodetool CLI available from any terminal

    • Environment Setup

    After installation, these variables are automatically configured:

    # Conda environment
export MAMBA_ROOT_PREFIX="$HOME/.nodetool/micromamba"
export PATH="$HOME/.nodetool/env/bin:$HOME/.nodetool/env/Library/bin:$PATH"
    Model cache directories
    
export HF_HOME="$HOME/.nodetool/cache/huggingface"
export OLLAMA_MODELS="$HOME/.nodetool/cache/ollama"

    System Info

    Check NodeTool environment and installed packages:

    nodetool info

    Output shows:

  • Version
  • Python version
  • Platform/Architecture
  • Installed AI packages (OpenAI, Anthropic, Google, HF, Ollama, fal-client)
  • Environment variables
  • API key status

    • ⚑ When to Use

    TriggerAction
    Run a NodeTool workflow and get structured output:
    ```bash
    # Run workflow interactively
    nodetool run my_workflow_id
    # Run and stream JSONL output
    nodetool run my_workflow_id --jsonl | jq -r '.[] | "\(.status) | \(.output)"'
    ```
    ### Package Creation
    Generate documentation for a custom package:
    ```bash
    # Scan for nodes and create package
    nodetool package scan
    # Generate complete documentation
    nodetool package docs
    ```
    ### Deployment
    Deploy a NodeTool instance to the cloud:
    ```bash
    # Initialize deployment config
    nodetool deploy init
    # Add RunPod deployment
    nodetool deploy add
    # Deploy and start
    nodetool deploy apply
    ```
    ### Model Management
    Check and manage cached AI models:
    ```bash
    # List all available models
    nodetool model list-hf-all
    # Inspect cache
    nodetool model hf-cache
    ```

    πŸ’‘ Examples

    # See system info
nodetool info
    List workflows
    
nodetool workflows list
    Run a workflow interactively
    
nodetool run 
    Start of chat interface
    
nodetool chat
    Start of web server
    
nodetool serve