--- title: "self-hosted-ai-starter-kit" type: "tool" slug: "n8n-io-self-hosted-ai-starter-kit" canonical_url: "https://www.graphcanon.com/tools/n8n-io-self-hosted-ai-starter-kit" github_url: "https://github.com/n8n-io/self-hosted-ai-starter-kit" homepage_url: "https://n8n.io" stars: 15031 forks: 3785 primary_language: null license: "Apache-2.0" categories: ["data-retrieval", "llm-frameworks", "ai-agents", "inference-serving", "vector-databases"] tags: ["starter-kit", "self-hosted", "ai", "low-code"] updated_at: "2026-07-07T18:29:59.250912+00:00" --- # self-hosted-ai-starter-kit > Self-hosted AI Starter Kit An open-source Docker Compose template initializing a local AI development environment with self-hosted n8n platform, Ollama, Qdrant, PostgreSQL. ## Facts - Repository: https://github.com/n8n-io/self-hosted-ai-starter-kit - Homepage: https://n8n.io - Stars: 15,031 · Forks: 3,785 · Open issues: 6 · Watchers: 182 - License: Apache-2.0 - Last pushed: 2026-01-06T14:08:21+00:00 ## Categories - [Data & Retrieval](/categories/data-retrieval.md) - [LLM Frameworks](/categories/llm-frameworks.md) - [AI Agents](/categories/ai-agents.md) - [Inference & Serving](/categories/inference-serving.md) - [Vector Databases](/categories/vector-databases.md) ## Tags starter-kit, self-hosted, ai集成, low-code ## Related tools - [ECC](/tools/affaan-m-ecc.md) - The agent harness performance optimization system (★ 226,962) - [hermes-agent](/tools/nousresearch-hermes-agent.md) - The self-improving AI agent built by Nous Research (★ 210,880) - [AutoGPT](/tools/significant-gravitas-autogpt.md) - AutoGPT: Build, Deploy, and Run AI Agents (★ 185,417) - [ollama](/tools/ollama-ollama.md) - Get up and running with Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and other models. 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Curated by , it combines the self-hosted n8n platform with a curated list of compatible AI products and components to quickly get started with building self-hosted AI workflows. > [!TIP] > [Read the announcement](https://blog.n8n.io/self-hosted-ai/) ### What’s included ✅ [**Self-hosted n8n**](https://n8n.io/) - Low-code platform with over 400 integrations and advanced AI components ✅ [**Ollama**](https://ollama.com/) - Cross-platform LLM platform to install and run the latest local LLMs ✅ [**Qdrant**](https://qdrant.tech/) - Open-source, high performance vector store with an comprehensive API ✅ [**PostgreSQL**](https://www.postgresql.org/) - Workhorse of the Data Engineering world, handles large amounts of data safely. ### What you can build ⭐️ **AI Agents** for scheduling appointments ⭐️ **Summarize Company PDFs** securely without data leaks ⭐️ **Smarter Slack Bots** for enhanced company communications and IT operations ⭐️ **Private Financial Document Analysis** at minimal cost ## Installation ### Cloning the Repository ```bash git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git cd self-hosted-ai-starter-kit cp .env.example .env # you should update secrets and passwords inside ``` ### Running n8n using Docker Compose #### For Nvidia GPU users ```bash git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git cd self-hosted-ai-starter-kit cp .env.example .env # you should update secrets and passwords inside docker compose --profile gpu-nvidia up ``` > [!NOTE] > If you have not used your Nvidia GPU with Docker before, please follow the > [Ollama Docker instructions](https://github.com/ollama/ollama/blob/main/docs/docker.md). ### For AMD GPU users on Linux ```bash git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git cd self-hosted-ai-starter-kit cp .env.example .env # you should update secrets and passwords inside docker compose --profile gpu-amd up ``` #### For Mac / Apple Silicon users If you’re using a Mac with an M1 or newer processor, you can't expose your GPU to the Docker instance, unfortunately. There are two options in this case: 1. Run the starter kit fully on CPU, like in the section "For everyone else" below 2. Run Ollama on your Mac for faster inference, and connect to that from the n8n instance If you want to run Ollama on your mac, check the [Ollama homepage](https://ollama.com/) for installation instructions, and run the starter kit as follows: ```bash git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git cd self-hosted-ai-starter-kit cp .env.example .env # you should update secrets and passwords inside docker compose up ``` ##### For Mac users running OLLAMA locally If you're running OLLAMA locally on your Mac (not in Docker), you need to modify the OLLAMA_HOST environment variable 1. Set OLLAMA_HOST to `host.docker.internal:11434` in your .env file. 2. Additionally, after you see "Editor is now accessible via: ": 1. Head to 2. Click on "Local Ollama service" 3. Change the base URL to "http://host.docker.internal:11434/" #### For everyone else ```bash git clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git cd self-hosted-ai-starter-kit cp .env.example .env # you should update secrets and passwords inside docker compose --profile cpu up ``` ## ⚡️ Quick start and usage The core of the Self-hosted AI Starter Kit is a Docker Compose file, pre-configured with network and storage settings, minimizing the need for additional installations. After completing the installation steps above, simply follow the steps below to get started. 1. Open in your browser to set up n8n. You’ll only have to do ``` --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/tools/n8n-io-self-hosted-ai-starter-kit`](/api/graphcanon/tools/n8n-io-self-hosted-ai-starter-kit) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_