{"data":{"slug":"n8n-io-self-hosted-ai-starter-kit","name":"self-hosted-ai-starter-kit","tagline":"Self-hosted AI Starter Kit template for local AI workflows","github_url":"https://github.com/n8n-io/self-hosted-ai-starter-kit","owner":"n8n-io","repo":"self-hosted-ai-starter-kit","owner_avatar_url":"https://avatars.githubusercontent.com/u/45487711?v=4","primary_language":null,"stars":15190,"forks":3807,"topics":["ai","ai-agents","low-code","self-hosted","starter-kit"],"archived":false,"github_pushed_at":"2026-07-23T11:28:09+00:00","maintenance_label":"Active","stars_delta_30d":94,"url":"https://www.graphcanon.com/tools/n8n-io-self-hosted-ai-starter-kit","markdown_url":"https://www.graphcanon.com/tools/n8n-io-self-hosted-ai-starter-kit.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/n8n-io-self-hosted-ai-starter-kit","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=n8n-io-self-hosted-ai-starter-kit","description":"The Self-hosted AI Starter Kit is an open-source template that quickly sets up a local AI environment. Curated by n8n, it provides essential tools for creating secure, self-hosted AI workflows.","homepage_url":"https://n8n.io","license":"Apache-2.0","open_issues":3,"watchers":181,"ai_summary":"Provides an open-source template to quickly set up a secure, self-hosted environment for creating AI workflows using Docker Compose.","readme_excerpt":"### Running n8n using Docker Compose\n\n#### For Nvidia GPU users\n\n```bash\ngit clone https://github.com/n8n-io/self-hosted-ai-starter-kit.git\ncd self-hosted-ai-starter-kit\ncp .env.example .env # you should update secrets and passwords inside\ndocker compose --profile gpu-nvidia up\n```\n\n> [!NOTE]\n> If you have not used your Nvidia GPU with Docker before, please follow the\n> [Ollama Docker instructions](https://docs.ollama.com/docker).\n\n---\n\n## ⚡️ Quick start and usage\n\nThe 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.\nAfter completing the installation steps above, simply follow the steps below to get started.\n\n1. Open <http://localhost:5678/> in your browser to set up n8n. You’ll only\n   have to do this once.\n2. Open the included workflow:\n   <http://localhost:5678/workflow/srOnR8PAY3u4RSwb>\n3. Click the **Chat** button at the bottom of the canvas, to start running the workflow.\n4. If this is the first time you’re running the workflow, you may need to wait\n   until Ollama finishes downloading Llama3.2. You can inspect the docker\n   console logs to check on the progress.\n\nTo open n8n at any time, visit <http://localhost:5678/> in your browser.\n\nWith your n8n instance, you’ll have access to over 400 integrations and a\nsuite of basic and advanced AI nodes such as\n[AI Agent](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/),\n[Text classifier](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.text-classifier/),\nand [Information Extractor](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.information-extractor/)\nnodes. To keep everything local, just remember to use the Ollama node for your\nlanguage model and Qdrant as your vector store.\n\n> [!NOTE]\n> This starter kit is designed to help you get started with self-hosted AI\n> workflows. While it’s not fully optimized for production environments, it\n> combines robust components that work well together for proof-of-concept\n> projects. You can customize it to meet your specific needs\n\n---\n\n## 📜 License\n\nThis project is licensed under the Apache License 2.0 - see the\n[LICENSE](LICENSE) file for details.","github_created_at":"2024-02-23T13:56:32+00:00","created_at":"2026-07-07T17:41:00.135939+00:00","updated_at":"2026-08-20T00:01:31.594106+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"developer-tools","name":"Developer Tools","url":"https://www.graphcanon.com/categories/developer-tools","markdown_url":"https://www.graphcanon.com/categories/developer-tools.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/developer-tools"}],"tags":[{"slug":"ai","name":"ai"},{"slug":"docker-compose","name":"docker-compose"},{"slug":"low-code","name":"low-code"},{"slug":"n8n","name":"n8n"},{"slug":"self-hosted","name":"self-hosted"},{"slug":"starter-kit","name":"starter-kit"}],"trust":{"provenance":{"is_fork":false,"github_id":762303728,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-20T00:01:30.856Z","maintenance":{"label":"Active","score":82,"methodology":"github_public_v1","releases_90d":0,"days_since_push":27,"last_release_at":null,"stars_delta_30d":94,"open_issues_delta_30d":-3},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:18:12.809Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-20T00:01:31.289Z"},"deploy":{"source":"dockerfile:docker-compose.yml","self_host":true,"observed_at":"2026-08-20T00:01:31.289Z","managed_saas":false},"has_docker":{"value":true,"source":"dockerfile:docker-compose.yml","observed_at":"2026-08-20T00:01:31.289Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-20T00:01:31.289Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"notes":["Ensure Nvidia GPU support is correctly configured if planning to utilize GPU acceleration."]},"constraints":null,"when_to_use":["* When you need a customizable, self-hosted environment for AI workflows using tools like n8n with minimal setup via Docker Compose.","* If you want to leverage GPU acceleration from Nvidia and are familiar with integrating GPUs in Docker environments, as the kit includes specific instructions for Nvidia GPU users.","* For proof-of-concept projects where you require a robust but not fully optimized environment for testing AI workflows locally."],"when_not_to_use":["* Avoid if your project requires full-scale production-ready setups; this starter kit is more fitted for early-stage development and prototyping, with customization needed to scale.","* Not suitable for users unfamiliar or uncomfortable working with Docker and setting up environments manually, including modifying `.env` files and potentially dealing with GPU setup instructions."],"source":"enrich:decision_facts","observed_at":"2026-07-11T15:01:20.170Z"},"constraint_facets":null,"decision_summary":[{"label":"Requirements","value":"Ensure Nvidia GPU support is correctly configured if planning to utilize GPU acceleration."},{"label":"Adopt for","value":"The Self-hosted AI Starter Kit by n8n offers a pre-configured Docker Compose setup for setting up local AI workflows."},{"label":"License detail","value":"The Self-hosted AI Starter Kit is open-source under the Apache-2.0 license."}]}}