SEC.01

The playbook

The run starts read-only: the recon probes decide what happens next. The steps that follow are adapted to the distribution and state found — a real machine is rarely clean.

1. 01reconHomebrew present? absolute path, prefix owner (brew refuses root: go through sudo -u <owner>), architecture
2. 02reconOllama already present (formula or Ollama.app)?
3. 03reconport 11434 free?
4. 04reconRAM and free disk (a 3B model ≈ 2 GB, 8B ≈ 5 GB)
5. 05actInstall Ollamaverify
6. 06actStart the serviceverify
7. 07actDownload the model (only if a model is provided)verify

SEC.02

What it verifies

Each step ships its own check. The run only moves on when the check passes, so what the recipe reports as done is what is actually on the server.

1. 01verifyInstall OllamaVerified byb=$(ls /opt/homebrew/bin/brew /usr/local/bin/brew 2>/dev/null | head -1); u=$(stat -L -f %Su "$b"); p=$(dirname "$(dirname "$b")"); "$p/bin/ollama" --version
2. 02verifyStart the serviceVerified bycurl -sf http://127.0.0.1:11434/api/version
3. 03verifyDownload the model (only if a model is provided)Verified byb=$(ls /opt/homebrew/bin/brew /usr/local/bin/brew 2>/dev/null | head -1); u=$(stat -L -f %Su "$b"); p=$(dirname "$(dirname "$b")"); "$p/bin/ollama" list | grep -c "${model}"

SEC.03

Guardrails

Non-negotiable instructions the run must respect, whatever it finds on the server.

SEC.04

Variables

What you choose before launching — the recipe fills in the rest.

SEC.05

How a recipe runs in Servor

Servor is zero-knowledge: the platform cannot execute anything on its own. When you launch this recipe, a run reads the reconnaissance, plans the steps and asks for your approval. Each approved command is signed by your browser — with a key the server never sees — then relayed verbatim to the agent, which verifies the signature locally before executing.

SEC.06

Deploy on Servor button

Maintain Ollama (macOS) or a project that needs it? Put this button in your README or on your site: one click and your users install it on their own server.

SEC.07

More ai / ml recipes

1. 01OllamaOllama to run local LLMs (NVIDIA GPU if present, CPU otherwise), API on 127.0.0.1, optional model pull.
2. 02JupyterLabJupyterLab via Docker, on 127.0.0.1 with a generated access token (access through an SSH tunnel).
3. 03Open WebUIOpen WebUI, a web interface for LLMs (Ollama), via Docker on 127.0.0.1, wired to the local Ollama.
4. 04NVIDIA drivers + CUDANVIDIA driver, CUDA toolkit and Docker Container Toolkit from the official repositories. Destructive: kernel modules, restart likely.
5. 05ComfyUI (Stable Diffusion)ComfyUI for image generation, installed from the official repository as a systemd service (NVIDIA GPU recommended, CPU possible).