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Self-hosted AI starter kit (by the n8n team) MCP Server

@cedricdcc

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cedricdcc

关于 Self-hosted AI starter kit (by the n8n team) MCP Server

pydantic agent workflow using mcp servers to test out advanced retrieval of linked data

Self-hosted AI starter kit (by the n8n team) MCP Server 配置

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Self-hosted AI starter kit (by the n8n team) MCP Server 工具

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概览

What is Self-hosted AI starter kit (by the n8n team)?

The Self-hosted AI starter kit is an open Docker Compose template that quickly bootstraps a fully featured Local AI and Low Code development environment. It combines the self-hosted n8n platform with curated AI products including Ollama, Open WebUI, Flowise, Qdrant, and PostgreSQL. This version by coleam00 adds Open WebUI and Flowise improvements and includes a pre-configured local RAG AI Agent workflow.

How to use Self-hosted AI starter kit (by the n8n team)?

Clone the repository, navigate to the local-ai-packaged directory, and run docker compose with the appropriate profile (--profile gpu-nvidia, --profile cpu, or without a profile for Mac). Then open http://localhost:5678/ to set up n8n and http://localhost:3000/ to set up Open WebUI. Configure credentials for Ollama, Postgres, Qdrant, and optionally Google Drive, then activate the included workflow and paste the n8n_pipe.py code into Open WebUI’s Functions.

Key features of Self-hosted AI starter kit (by the n8n team)

  • Includes self-hosted n8n with over 400 integrations and AI components
  • Bundles Ollama for running local LLMs like Llama3.1
  • Provides Open WebUI for interacting with models and n8n agents
  • Includes Flowise for no/low code AI agent building
  • Ships with Qdrant vector store and PostgreSQL database
  • Pre-loaded local RAG AI Agent workflow auto-installed on first run

Use cases of Self-hosted AI starter kit (by the n8n team)

  • Building and testing self-hosted AI workflows with local language models
  • Creating a private ChatGPT-like interface for interacting with n8n agents
  • Developing proof-of-concept AI applications that keep data entirely on-premises
  • Experimenting with RAG pipelines using local vector stores and LLMs

常见问题

1

What hardware do I need?

The kit supports Nvidia GPUs (via Docker profile), Mac/Apple Silicon (CPU-only or with external Ollama), and CPU-only environments for all other setups.

2

How do I upgrade the starter kit?

Run `docker compose --profile <profile> pull` followed by `docker compose create && docker compose --profile <profile> up`, using the same profile as your initial installation.

3

Where are local files stored?

A shared folder is mounted to the n8n container at `/data/shared`. Nodes like Read/Write Files from Disk, Local File Trigger, and Execute Command can access files there.

4

How do I connect to Ollama from n8n?

For Docker-based setups, use `http://ollama:11434` as the Ollama URL. For Mac users running Ollama natively, use `http://host.docker.internal:11434/`.

5

Is this production-ready?

The starter kit is designed to help get started with self-hosted AI workflows for proof-of-concept projects and is not fully optimized for production environments, though it uses robust components.

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