Container Host AIops (preview)

Disclaimer: Community-maintained open-source project. Not affiliated with, endorsed by, or sponsored by Docker, Inc., Portainer.io, or any container-platform vendor. "Docker", "Portainer" and all product/trademark names belong to their respective owners. MIT licensed.

Governed AI-ops for non-orchestrator container hosts — the Docker Engine API (over a local unix socket or a TCP host) and Portainer (its management API, which also proxies Docker) — with a built-in governance harness: unified audit log, policy engine, token/runaway budget guard, undo-token recording, and graduated-autonomy risk tiers. Multi-platform by construction: a registry keyed by platform means a per-target platform field (docker / portainer) selects the API shape, and another host family could be added later without touching the ops/CLI/MCP layers. Preview — mock-validated only, not verified against a live Docker daemon or Portainer server.

What it does

Three flagship signature analyses, plus the guarded reads and writes around them:

• Restart-loop RCA — inspect containers for restart count + exit code, flag the crash-looping ones (restartCount over threshold, or restarting/dead, or a non-zero exit), and map each to a likely cause + action from the exit code (137 OOM/SIGKILL, 143 SIGTERM, 139 segfault, 127 bad entrypoint, …), with a tail of logs. Every ranking carries its numbers, not a black-box verdict.
• Resource-pressure analysis — a one-shot CPU%/memory% sample per running container vs its configured limits, flagging each "near" (≥ 80% of a threshold) or "over", with a recommendation (raise a limit, set a missing memory limit, scale out).
• Image & volume bloat — dangling images + dangling volumes + build cache from system/df, totalled into prune candidates with reclaimable bytes.

What works

• CLI (container-host-aiops ...): init, overview, container, image, volume, network, system, stack, analyze, manage, secret, doctor, mcp.
• MCP server (container-host-aiops mcp or container-host-aiops-mcp): 34 tools (26 read, 8 write), every one wrapped with the bundled @governed_tool harness.
• Connection layer: Docker over a unix socket (httpx.HTTPTransport(uds=...)) or a TCP host; Portainer over HTTPS with an X-API-Key token that also proxies the Docker API of a managed endpoint. A local Docker socket needs no secret — the socket's file permissions are the boundary.
• Encrypted credentials: the Portainer API token lives in an encrypted store ~/.container-host-aiops/secrets.enc (Fernet + scrypt) — never plaintext on disk. Unlock with a master password from CONTAINER_HOST_AIOPS_MASTER_PASSWORD (MCP/CI) or an interactive prompt (CLI).
• Reversibility: mutating writes fetch the real before-state first and record a faithful inverse (stop↔start; update_container restores prior CPU/memory limits). Irreversible ops (remove_container, prune_images, prune_volumes, recreate_stack) capture the before-state for audit but declare no undo.
• Safety: every state-changing CLI op supports --dry-run and requires double confirmation; every write MCP tool takes a dry_run preview — and prune previews list what would be removed + reclaimable bytes before doing it.

Capability matrix (34 MCP tools)

Domain	Tools	Count	R/W
Overview	overview	1	read
Containers	list_containers, inspect_container, container_logs, container_stats, container_top, container_restart_summary	6	read
Images	list_images, inspect_image, dangling_images, image_disk_usage	4	read
Volumes	list_volumes, inspect_volume, dangling_volumes	3	read
Networks	list_networks, inspect_network	2	read
System	system_info, system_version, system_df, system_events	4	read
Stacks (Portainer)	list_endpoints, list_stacks, stack_detail	3	read
Analyses (flagship)	restart_loop_rca, resource_pressure_analysis, image_and_volume_bloat	3	read
Writes	remove_container, prune_images, prune_volumes, recreate_stack	4	write (high)
	restart_container, stop_container, start_container, update_container	4	write (medium)

The three analyses accept injected data for offline analysis, or pull live from a configured target. Stacks/endpoints require a portainer target.

Quick start

uv tool install container-host-aiops          # or: pipx install container-host-aiops
container-host-aiops init                      # wizard: add a Docker socket or Portainer target
container-host-aiops doctor                    # verify config, secrets, connectivity
container-host-aiops overview                  # one-shot host health
container-host-aiops analyze restart-loop      # crash-looping containers + cause/action
container-host-aiops container list --running  # running containers

Run as an MCP server (stdio):

export CONTAINER_HOST_AIOPS_MASTER_PASSWORD=...   # only needed for Portainer targets
container-host-aiops-mcp

Governance

Every MCP tool passes through the bundled @governed_tool harness:

• Audit — every call (params, result, status, duration, risk tier, approver, rationale) is logged to ~/.container-host-aiops/audit.db (relocatable via CONTAINER_HOST_AIOPS_HOME).
• Budget / runaway guard — token and call budgets trip a circuit breaker.
• Risk tiers — graduated autonomy; high-risk ops (remove / prune / recreate) can require a named approver.
• Undo recording — reversible writes record an inverse descriptor built from the fetched before-state.

Scope

This is the container-host member of the AIops-tools family (governed AI-ops with audit + budget + undo + risk tiers), for single-host Docker / Portainer. It is deliberately NOT for a cluster orchestrator, a hypervisor, a storage appliance, a backup product, or OT / industrial edge — those are separate tools/lines.

Missing a capability?

Coverage is intentionally a curated subset of the Docker Engine + Portainer APIs. Missing a call, or want another container host family? Open an issue or PR — contributions welcome.

Status

Preview — mock-validated only, not verified against a live Docker daemon or Portainer server. The API paths are modelled from the public API shape and need live verification. container-host-aiops doctor is the fastest live check.