Open-source, node-based visual editor for building AI agents, multimodal pipelines, and RAG systems locally or in the cloud.
Nodetool is an open-source visual builder that lets you create AI workflows by connecting drag-and-drop nodes on a canvas. Build LLM agents, image and video pipelines, document intelligence systems, and automations without writing code. It runs locally on your machine for full privacy, supports models from OpenAI, Anthropic, Google, Hugging Face, Ollama, and more, and can scale to the cloud when needed. Licensed under AGPL-3.0 and available on macOS, Windows, and Linux.
Yes. Nodetool is open-source software released under the AGPL-3.0 license. You can download and use it at no cost. The only expenses come from third-party cloud AI providers (like OpenAI or Anthropic) if you choose to use their APIs. Running models locally with Ollama or other local backends is completely free.
For local AI model execution, you need either an NVIDIA GPU with CUDA driver 525.60+ (Linux) or 527.41+ (Windows), or an Apple Silicon Mac (M1 or later). CPU-only mode works too but will be significantly slower for model inference. Plan for at least 20GB of free disk space for model downloads.
Yes. You can run Nodetool in cloud-only mode, using API services from providers like OpenAI, Anthropic, or Google without any local GPU. You can also run smaller models on CPU, though performance will be limited.
ComfyUI focuses specifically on image and media generation workflows. Nodetool covers a broader range of AI tasks including LLM agents, real-time streaming, RAG systems, document processing, and general automation, in addition to media generation.
n8n is a general-purpose workflow automation tool built for business processes and API integrations. Nodetool is specialized for AI workloads with native support for model management, local LLMs, multimodal processing, RAG, and sandboxed code execution.
Nodetool supports models from OpenAI, Anthropic, Google, Hugging Face, Groq, Together, Replicate, Cohere, and others. For local execution, it supports Ollama, MLX, and GGML/GGUF model formats. You can mix local and cloud models in the same workflow.
No coding is needed for most workflows. You build pipelines visually by connecting nodes on a canvas. However, understanding concepts like prompt engineering, API keys, and model configurations will help you get more out of complex workflows.
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