Open Forge

open-forge — self-host any open-source app

---

name: open-forge description: Automate self-hosting of open-source apps on cloud infrastructure the user owns. Use when the user asks to "self-host", "deploy to my own cloud", "install X on AWS / Lightsail / EC2 / Azure / Hetzner / DigitalOcean / GCP / Oracle Cloud / Hostinger / Raspberry Pi / Kubernetes / Fly.io / Render / Railway / Northflank / exe.dev", "set up my own Ghost blog / Mastodon / WordPress / Nextcloud", wants to deploy the self-hosted personal AI agent OpenClaw (openclaw.ai — NOT the Captain Claw platformer game) or Hermes-Agent (Nous Research's self-improving AI agent at github.com/NousResearch/hermes-agent), wants to run Ollama (local-LLM inference server at ollama.com — pairs with every AI agent / chat UI as an OpenAI-compatible provider), wants to run Open WebUI (feature-rich self-hosted ChatGPT-like UI at github.com/open-webui/open-webui — pairs natively with Ollama and any OpenAI-compatible backend; adds RAG, web search, image gen, voice, multi-user), wants to run Stable Diffusion WebUI / Automatic1111 / A1111 (the most-popular open-source AI image generator at github.com/AUTOMATIC1111/stable-diffusion-webui — text-to-image, img2img, inpainting, ControlNet, LoRA; pairs with Open WebUI as an image-gen backend), wants to run ComfyUI (node-based AI image / video generation at github.com/comfyanonymous/ComfyUI — power-user alternative to A1111 with workflow graphs; same models, different UX; pairs with Open WebUI as image-gen backend), wants to deploy Dify (open-source LLMOps + AI app builder at github.com/langgenius/dify — visual workflow builder, RAG, multi-tenant; the "build a SaaS-grade AI app" platform, different category from chat UIs), wants to deploy LibreChat (multi-provider chat UI with deep enterprise plumbing at github.com/danny-avila/LibreChat — alternative to Open WebUI for teams; multi-user with social logins, per-user balance + transactions, agents + MCP, dedicated rag_api), wants to deploy AnythingLLM (RAG-focused workspace + agent platform at github.com/Mintplex-Labs/anything-llm — drop-in PDFs + URLs + GitHub repos, ask questions over them; built-in LanceDB; Desktop App + Docker + 8 cloud one-clicks), wants to install Aider (AI pair-programming CLI at github.com/Aider-AI/aider — runs in the terminal next to a git repo, edits files via diffs, auto-commits; pairs with any LLM provider including Ollama for local), wants to deploy vLLM (production-grade LLM inference server at github.com/vllm-project/vllm — high-throughput multi-tenant serving with PagedAttention + tensor parallelism + prefix caching; NVIDIA / AMD / Intel / CPU; Docker / Kubernetes / Helm / PaaS), wants to deploy Langfuse (open-source LLM engineering platform at github.com/langfuse/langfuse — observability, evals, prompt management, datasets, scoring; v3 six-service architecture with Postgres + ClickHouse + Redis + S3; Docker Compose, Kubernetes Helm chart, first-party Terraform modules for AWS / GCP / Azure, Railway one-click), or names any combination of an open-source app and a cloud provider. Walks the user through provisioning, DNS, TLS, outbound email (SMTP), and inbound email, in phases that are resumable across sessions via a state file at ~/.open-forge/deployments/.yaml. Supported today: Ghost on AWS Lightsail (Bitnami blueprint); OpenClaw via every upstream-blessed path documented at docs.openclaw.ai/install/* — AWS Lightsail blueprint, Docker Compose, Podman, Kubernetes (Kustomize), native installers (install.sh / install-cli.sh / install.ps1), ClawDock, Ansible, Nix, Bun, plus per-host adapters for AWS EC2 / Azure / Hetzner / DigitalOcean / GCP / Oracle Cloud / Hostinger / Raspberry Pi / macOS-VM (Lume) / BYO Linux server / localhost / Fly.io / Render / Railway / Northflank / exe.dev. More projects and infras added under references/projects/ and references/infra/. ---

open-forge

Overview

Walk a user from "I have a cloud account and a domain" to "working app at https://my.domain with TLS and mail." Load the appropriate project recipe and infra adapter based on the user's stated intent; run phases sequentially; record state so the user can resume later.

> Platform note: this skill is designed for Claude Code but the content is platform-agnostic. Tool names like AskUserQuestion, WebFetch, and mcp__github__* are Claude Code-specific — read them as capabilities (structured-choice prompt, URL fetch, GitHub API) and use whichever equivalent your platform exposes. See [docs/platforms/](../../../../docs/platforms/) in the repo for per-platform integration guides (Codex / Cursor / Aider / Continue / generic).

Operating principle

Claude does the work; the user makes the choices. open-forge replaces the traditional "read a README, copy-paste 30 lines of bash, debug for hours" experience with a guided chat where Claude executes everything via the user's local CLI tools (aws, ssh, jq, curl) and only stops to ask when input is genuinely required.

What this means in practice:

• Run, don't print. When a recipe contains a bash block, Claude executes it. Announce it in one sentence first ("Opening port 22 in the Lightsail firewall now."), then run. Don't paste the block into chat for the user to run.
• Ask for choices and credentials only. Things only the user can decide or provide: AWS profile name, domain choice, canonical www-vs-apex, SMTP API key, model provider preference. Everything else (which jq command to run, which sed pattern to apply, which IAM script URL to fetch) Claude figures out from the recipe.
• One question at a time when possible. Use a structured-choice prompt for multiple-choice / single-select (Claude Code: AskUserQuestion; on other platforms, ask in prose with options listed). Reserve free-text questions for things like API keys and domain names. Avoid wall-of-questions forms.
• Auto-install with confirmation, not silently. If jq or aws is missing, propose the install command, get one-line approval, then run it. Never sudo apt-get install without asking.
• The recipe files in references/projects/ and references/infra/ are guidance for Claude, not pages for the user to read. Keep that lens when extending or refactoring.

What's supported

Check references/projects/ and references/infra/ for available recipes/adapters. As of this writing:

Supported software:

| Software | What it is | |---|---| | Ghost | Self-hosted blogging platform | | OpenClaw | Self-hosted personal AI agent (openclaw.ai — NOT the Captain Claw platformer game) | | Hermes-Agent | Self-improving personal AI agent from Nous Research (github.com/NousResearch/hermes-agent). Native (scripts/install.sh), Docker, Nix, manual-dev, Termux (Android), Homebrew. Includes hermes claw migrate for OpenClaw users. | | Ollama | Local-LLM inference server (ollama.com). Foundation layer — pairs with OpenClaw / Hermes / Open WebUI / LibreChat / Aider / etc. as an OpenAI-compatible provider. Native (install.sh / install.ps1 / .dmg / .exe), Docker (CPU + NVIDIA + AMD ROCm + Vulkan), Kubernetes (community Helm chart), Homebrew, Nix, Pacman. | | Open WebUI | Feature-rich web UI for any OpenAI-compatible LLM backend (github.com/open-webui/open-webui). Multi-user, RAG, web search, image gen, voice, MCP. Pairs naturally with Ollama. Docker (:main / :cuda / :ollama / :dev tags), docker-compose (with bundled or external Ollama), pip (Python 3.11), Kubernetes (community Helm). | | Stable Diffusion WebUI (A1111) | The most-popular open-source AI image generator (github.com/AUTOMATIC1111/stable-diffusion-webui). Pairs with Open WebUI as an image-gen backend. Native (webui.sh Linux/macOS, webui-user.bat Windows, sd.webui.zip one-click), GPU paths for NVIDIA CUDA / AMD ROCm Linux / AMD DirectML Windows fork / Apple Silicon MPS, plus community-maintained Docker images (AbdBarho recommended). | | ComfyUI | Node-based AI image / video generation (github.com/comfyanonymous/ComfyUI). Power-user alternative to A1111; same models, workflow-graph UX. Pairs with Open WebUI as image-gen backend. Desktop App (Windows/macOS), Windows portable 7z (NVIDIA / AMD / Intel variants), comfy-cli, manual install, plus broad GPU support (NVIDIA CUDA, AMD ROCm Linux + Windows nightly, Intel Arc XPU, Apple Silicon MPS) and community Docker (AbdBarho comfy profile, yanwk/comfyui-boot). | | Dify | Open-source LLMOps + AI app builder platform (github.com/langgenius/dify). Visual workflow builder, RAG with many vector-DB backends (Weaviate / Qdrant / Milvus / pgvector / Elasticsearch / OpenSearch / Couchbase / Chroma / +more), multi-tenant, plugin marketplace. Different category from chat UIs — Dify is the platform for building AI products. Docker Compose (canonical, ~12 services), Kubernetes via community Helm, source code, aaPanel one-click, plus cloud templates (Azure / GCP Terraform, AWS CDK for EKS/ECS, Alibaba Computing Nest). | | LibreChat | Multi-provider chat UI with deep enterprise plumbing (github.com/danny-avila/LibreChat). Multi-user with social logins (GitHub / Google / Discord / OIDC / SAML / Apple / Facebook), per-user balance + transactions, agents + assistants + MCP, RAG via pgvector + dedicated rag_api, web search, TTS/STT. Alternative to Open WebUI for teams. Docker Compose dev (docker-compose.yml), Docker Compose prod (deploy-compose.yml + Nginx), npm / source, first-party Helm chart (helm/librechat/ v2.0.2), plus one-click deploys for Railway / Zeabur / Sealos. | | AnythingLLM | Open-source RAG-focused workspace + AI agent platform (github.com/Mintplex-Labs/anything-llm). Workspace-style "drop a folder of PDFs, ask questions over them" UX with built-in LanceDB vector store (or external Pinecone / Weaviate / Qdrant / Chroma / Milvus / Astra / pgvector), built-in agents, MCP support, multi-user, embeddable chat widget. Docker (canonical, docker/HOW_TO_USE_DOCKER.md), Desktop App (Mac / Windows / Linux installers), bare-metal source install (per BARE_METAL.md, "not supported by core team" — flagged), plus upstream-published one-click cloud deploys for AWS CloudFormation / GCP Cloud Run / DigitalOcean Terraform / Render / Railway / RepoCloud / Elestio / Northflank. | | Aider | AI pair-programming CLI (github.com/Aider-AI/aider). Different category — runs in the developer's terminal alongside their git repo, edits files via diffs, auto-commits per change. Pairs with any LLM provider (Anthropic / OpenAI / DeepSeek / Gemini / OpenRouter / Ollama / vLLM / OpenAI-compatible). aider-install (recommended, isolated Python 3.12 env), uv-based one-liner script (Mac / Linux / Windows), uv direct, pipx, plain pip, plus Docker (paulgauthier/aider + paulgauthier/aider-full), GitHub Codespaces, and Replit. | | vLLM | Production-grade LLM inference server (github.com/vllm-project/vllm). Different niche from Ollama (single-user / hobby) — vLLM is for high-throughput multi-tenant serving with PagedAttention, tensor parallelism, prefix caching. NVIDIA CUDA (canonical) + AMD ROCm + Intel XPU/Gaudi + CPU variants (x86 / ARM / Apple Silicon / s390x), Docker (vllm/vllm-openai), Kubernetes (raw manifests + first-party Helm chart + LeaderWorkerSet for distributed inference), plus upstream PaaS cookbooks (SkyPilot / RunPod / Modal / Cerebrium / dstack / Anyscale / Triton). | | Langfuse | Open-source LLM engineering platform (github.com/langfuse/langfuse). LLM observability + evaluation + prompt management + datasets + scoring; cross-cutting layer that pairs with vLLM / Ollama (inference) and Open WebUI / LibreChat / AnythingLLM / Dify / Aider (apps). v3 architecture is six services (web, worker, Postgres, ClickHouse, Redis, MinIO/S3). Docker Compose (local + single-VM), Kubernetes Helm chart (langfuse/langfuse-k8s, recommended for prod), first-party Terraform modules for AWS (EKS + Aurora + ElastiCache + S3 + ALB), GCP (GKE + Cloud SQL + Memorystore + GCS + LB), Azure (AKS + PG-Flex + Redis + Storage + App Gateway), plus upstream-published Railway one-click. |

Supported infras (under references/infra/):

| Cloud / where | Adapter | |---|---| | AWS | aws/lightsail.md (Ghost Bitnami + OpenClaw blueprints), aws/ec2.md (general-purpose VM) | | Azure | azure/vm.md (Bastion-hardened, no public IP) | | Hetzner Cloud | hetzner/cloud-cx.md (CX-line VPS via hcloud) | | DigitalOcean | digitalocean/droplet.md (Droplet via doctl) | | GCP Compute Engine | gcp/compute-engine.md (VM via gcloud) | | Oracle Cloud | oracle/free-tier-arm.md (Always-Free A1.Flex ARM + Tailscale) | | Hostinger | hostinger.md (managed via hPanel — no CLI) | | Raspberry Pi | raspberry-pi.md (Pi 4/5 64-bit, ARM64) | | macOS VM (Apple Silicon) | macos-vm.md (Lume; for iMessage via BlueBubbles) | | Any Linux VM (other providers, on-prem) | byo-vps.md (SSH-only, no cloud APIs) | | Your own machine | localhost.md (Claude runs commands directly) | | Fly.io | paas/fly.md (fly.toml + persistent volume; public or private mode) | | Render | paas/render.md (render.yaml Blueprint, one-click) | | Railway | paas/railway.md (one-click template) | | Northflank | paas/northflank.md (one-click stack) | | exe.dev | paas/exe-dev.md (Shelley agent or manual nginx) |

Supported runtimes (under references/runtimes/):

| Runtime | Notes | |---|---| | Docker | docker.md — install Docker on host + lifecycle via docker-compose. Reusable across every infra. | | Podman | podman.md — rootless Docker-compatible alternative; Quadlet (systemd-user) supported. Reusable across every Linux/macOS infra. | | Native | native.md — OS prereqs, systemd / launchd / Scheduled-Tasks lifecycle, reverse-proxy guidance. Covers install.sh (macOS / Linux / WSL2), install-cli.sh (local-prefix, no root), and install.ps1 (native Windows). | | Kubernetes | kubernetes.md — kubectl + Kustomize (preferred, what openclaw upstream uses) and Helm orchestration. open-forge does not provision clusters — point kubectl at one and we'll deploy into it. | | Vendor blueprints | Bundled into infra adapters (e.g. Lightsail Ghost-Bitnami, Lightsail OpenClaw) — runtime choice is the vendor's |

Selection — ask three questions

Before provisioning, establish three things by asking (or inferring from the user's prompt):

1. What to host? → loads references/projects/.md
2. Where to host? → loads references/infra//.md or references/infra/{byo-vps,localhost}.md
3. How to host? → loads the matching references/runtimes/.md (skipped if the infra bundles the runtime, e.g. vendor blueprints)

The how question is dynamically generated from (software, where) — each project lists its "Compatible combos" table in the project recipe, and the options shown are filtered by the user's where answer. If the user's initial prompt already names a clear infra ("deploy to Lightsail" → AWS), announce the inferred choice and continue — don't re-ask. Ask a structured-choice question only when genuinely ambiguous.

Then immediately load references/modules/preflight.md and run its steps. Preflight is combo-aware — it only installs / validates what the chosen tuple actually needs (AWS CLI only when infra ∈ AWS, Docker only when runtime = docker, nothing extra on localhost).

Goal-shaped requests → curated bundles

If the user describes a goal rather than a single piece of software (e.g. "set up an AI homelab", "I want a privacy stack for my home network"), check [references/bundles/](references/bundles/) for a matching curated bundle before falling through to single-software routing. Bundles are recipe-of-recipes that pair commonly-co-deployed apps with cross-software wiring already worked out.

| Bundle | Goal | Constituent recipes | |---|---|---| | bundles/ai-homelab.md | Private LLM + chat UI + RAG workspace + pair-programming | Ollama · Open WebUI

…

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: zhangqi444
• Source: zhangqi444/open-forge
• License: MIT

Install and usage instructions live in the source repository linked above.