Container Host AIops

Name: Container Host AIops
Author: AIops-tools

by AIops-toolsversion 0.14.0i★ 1iRuns on your computer

Registry nameio.github.AIops-tools/container-host-aiops

How to install

What it does

Governed Docker + Portainer container-host ops: reads, RCA analyses, guarded writes. 38 tools.

Connects Runs on your computer
Account or key No key needed
Category Developer tools

Install

Pick the AI app you use, then copy the settings.

Passed 3/3 checks · Runs on your computer

First: which AI do you use?

ClaudeWeb · app · phoneChatGPTWebClaude CodeTerminalCursorCode editorVS CodeCode editorOtherOther apps

Pick your app and the steps appear below.

Works with Claude, with some setup first

Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Open the Claude desktop app’s settings file
SettingsDeveloperEdit Config
Done

Paste these settings and save the file

{
  "mcpServers": {
    "container-host-aiops": {
      "command": "uvx",
      "args": [
        "container-host-aiops"
      ]
    }
  }
}

Done

Quit Claude and open it again
Done
Try it
Use Container Host AIops and tell me what you can do for me, then show me one thing
✓ If Claude says it is using Container Host AIops or shows a Container Host AIops tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

ChatGPT cannot connect Container Host AIops yet

Container Host AIops runs on your computer, but ChatGPT can only connect servers that run on the web

What you can do instead

A · Use an app that can connect Container Host AIops

Steps for Claude →Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
Steps for Claude Code →Install Python (uv) on your computer first (one time)
Steps for Cursor →Install Python (uv) on your computer first (one time)
Steps for VS Code →Install Python (uv) on your computer first (one time)

B · Others in Developer tools that work with ChatGPT

Picked from the most used in the same category, only ones that connect by address with no key

Sentry✓ ChatGPT
Compiler Explorer✓ ChatGPT
GitDiagram✓ ChatGPT

Works with Claude Code, with some setup first

Install Python (uv) on your computer first (one time)

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Open Terminal
Mac: press Command+Space and type Terminal · Windows: open PowerShell
Done

Paste this command and press Enter

claude mcp add --scope user container-host-aiops -- uvx container-host-aiops

Done

Type /mcp in Claude Code
You should see Container Host AIops listed as connected
Done
Try it
Use Container Host AIops and tell me what you can do for me, then show me one thing
✓ If Claude Code says it is using Container Host AIops or shows a Container Host AIops tool in the answer, you are connected

Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with Cursor, with some setup first

Install Python (uv) on your computer first (one time)

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Click this button to open Cursor
Open in Cursor
Cursor asks you to confirm; click Install
Done
Open the AI chat in Cursor in Agent mode
Done
Try it
Use Container Host AIops and tell me what you can do for me, then show me one thing
✓ If Cursor says it is using Container Host AIops or shows a Container Host AIops tool in the answer, you are connected

Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Works with VS Code, with some setup first

Install Python (uv) on your computer first (one time)

Install Python (uv)
One time only; it works for every server that needs Python (uv)
Open the Python (uv) download page ↗
Done
Click this button to open VS Code
Open in VS Code
VS Code asks you to confirm; click Install
Done
Open the AI chat in VS Code in Agent mode
Done
Try it
Use Container Host AIops and tell me what you can do for me, then show me one thing
✓ If VS Code says it is using Container Host AIops or shows a Container Host AIops tool in the answer, you are connected

Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version

Other apps that use MCP, such as Windsurf, Zed or Gemini CLI, each add servers differently. See how in the app list.

See every app that uses MCP →

JSON settings are under “For developers” below

Stuck? Ask people who use Container Host AIops💬 Discussion →

For developers: Terminal commands and JSON settings

Installed on your computer

Claude Code

claude mcp add --scope user container-host-aiops -- uvx container-host-aiops

Claude Desktop (claude_desktop_config.json)

{
  "mcpServers": {
    "container-host-aiops": {
      "command": "uvx",
      "args": [
        "container-host-aiops"
      ]
    }
  }
}

Cursor (~/.cursor/mcp.json)

{
  "mcpServers": {
    "container-host-aiops": {
      "command": "uvx",
      "args": [
        "container-host-aiops"
      ]
    }
  }
}

VS Code (mcp.json)

{
  "servers": {
    "container-host-aiops": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "container-host-aiops"
      ]
    }
  }
}

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

At a glance

GitHub stars i: 1
Downloads per weeki: 61/wk
Licence i: MIT
Connection: Runs on your computer
Transport: stdio
Latest versioni: 0.14.0
Categoryi: Developer tools
Published to registryi: Oct 30, 2026
Code last changedi: Oct 30, 2026
Maker: AIops-tools
Packages: pypi: container-host-aiops
Repo: AIops-tools/Container-Host-AIops
Registry status: Active

Which apps can use it

Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.

Run on your computer in

Claude Goose LM Studio Msty Studio Cherry Studio Cursor VS Code + GitHub Copilot Visual Studio Windsurf (Devin Desktop)Zed Kiro Cline Continue JetBrains AI Assistant Claude Code Codex CLI Gemini CLI OpenCode nodecode Warp LibreChat Raycast

All apps, with pros and cons →

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 12, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account AIops-tools, which owns the repo
✓ Pass
Still maintained
Code last changed 13 days ago
✓ Pass
Has a licence
Uses MIT
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Discussion

Ask, share a tip or report that it does not work. Sorted by what people marked helpful.

No posts yet. Be the first to ask or share.

Posts here are written by users, not the PopNx team.

User reviews

No reviews yet

Compared with others in Developer toolsi

More stars than 69% of the other 5802 servers in this category
Published to the registry more recently than 64% of the other 5802 servers in this category
Basic checks equal to or better than 100% of the other 5802 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Container Host AIops safe?

It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed 13 days ago, and the latest version (0.14.0) reached the registry 13 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: REA, GitHub, Serena MCP: the IDE for your agent

Others in the same category

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

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GitHub

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Container Host AIops

Audit availability: Real writes require a committed pending audit row and stop before contacting the platform if storage is unavailable. Reads and previews may continue with a warning; new audit rows store outcome summaries rather than full responses.

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), Portainer (its management API, which also proxies Docker), and Podman (a rootful/rootless service socket speaking the Docker-compatible API plus libpod-native endpoints) — with a built-in governance harness: a unified audit log over both MCP and CLI, a runaway/budget safety guard, and undo-token recording. It records every operation; it does not decide whether a write is permitted — that is the agent's or the account's call. Multi-platform by construction: a registry keyed by platform means a per-target platform field (docker / portainer / podman) selects the API shape, and another host family could be added later without touching the ops/CLI/MCP layers. Exercised against a live Docker Engine 27.5.1 daemon (doctor, overview, the three flagship analyses, and a governed stop_container with audit + undo recorded); the Portainer and Podman API paths are covered by the mock suite only.

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, pod, analyze, manage, secret, doctor, mcp.
MCP server (container-host-aiops mcp or container-host-aiops-mcp): 38 tools (29 read, 9 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; Podman over its rootful/rootless service socket (autodetected: $XDG_RUNTIME_DIR/podman/podman.sock first, then /run/podman/podman.sock) speaking the Docker-compat layer (paths reused wholesale) plus libpod-native endpoints. A local Docker/Podman 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.

What this tool does, and does not, decide

It delivers container-host operations — reads and writes — accurately and efficiently, and records every one of them. It does not decide whether a write is allowed to happen. That is the agent's judgement, or the permission of the account you connect it with: point it at a Docker socket mounted read-only, or a Portainer account without write scope, and the writes fail at the server — the place that actually owns the permission.

So there is no read-only switch, no policy file, no approval gate to configure. The one thing the tool guarantees is that nothing is silent: every call, over MCP and over the CLI alike, lands an audit row in ~/.container-host-aiops/audit.db, and destructive writes still capture their before-state and record an inverse where one exists.

Each tool declares a risk_level, kept in agreement with its [READ]/[WRITE]

documentation tag by a test, and carried into the audit row as a descriptive

tier — so a reviewer can see at a glance that a row was a high-risk delete. It

is a label, not a gate.

Capability matrix (38 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	`list_endpoints`, `list_stacks`, `stack_detail` (Portainer), `list_compose_stacks` (docker+podman)	4	read
Pods (Podman)	`list_pods`	1	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. list_endpoints/list_stacks/stack_detail require a portainer target; list_compose_stacks (Compose project rollup by the com.docker.compose.project label, with per-stack health) works on docker or podman; list_pods requires a podman target (Docker/Portainer have no pod concept).

Platform support matrix

Capability	docker	portainer	podman
Container / image / volume / network / system reads	✅	✅ (proxied)	✅ (compat)
Flagship analyses (restart-loop RCA, resource pressure, bloat)	✅	✅	✅ (compat)
Lifecycle + prune writes (stop/start/restart/remove/update/prune)	✅	✅	✅ (compat)
Compose-stack rollup (`list_compose_stacks`)	✅	✅ (proxied)	✅
Portainer endpoints / stacks / `recreate_stack`	—	✅	—
Podman pods (`list_pods`, libpod)	—	—	✅

Quick start

As a Claude Code plugin

One install gives an agent both the skill and the MCP server:

/plugin marketplace add AIops-tools/marketplace

/plugin install container-host-aiops@aiops-tools

The MCP server is fetched with uv and pinned to the package version this plugin declares, so an audit row can be traced back to the code that wrote it. Credentials are still configured with container-host-aiops init — see below.

As an OpenClaw plugin

The same bundle is published on ClawHub, where one install delivers the skill and its MCP server together:

openclaw plugins install clawhub:@zw008/container-host-aiops

openclaw skills info container-host-aiops # expect: Visible to model: yes

Restart the OpenClaw gateway afterwards so it loads the plugin. The MCP server is fetched with uv, pinned to this exact release, so uvx has to be on PATH — without it the skill still installs but reports Visible to model: no. Credentials are configured exactly as below.

As a CLI or standalone MCP server

uv tool install container-host-aiops          # or: pipx install container-host-aiops

container-host-aiops init # wizard: add a Docker/Podman 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

Where that password then lives: an exported variable is readable by

every process this shell starts and is recorded by shell history. On a

shared or long-lived host, prefer the interactive prompt, or inject it from

a secret manager for the life of the one command that needs it.

Governance

Every operation — MCP and CLI — passes through the bundled @governed_tool harness. It records; it does not authorize (see above).

Audit — every call (params, outcome summary, status, duration, risk tier, and any operator-supplied approver/rationale) is logged to ~/.container-host-aiops/audit.db (relocatable via CONTAINER_HOST_AIOPS_HOME). The CLI writes the same row the MCP path does — there is no unaudited entry point.
Runaway guard — a safety backstop, not an authorization gate: the same call hammered in a tight loop trips a circuit breaker so a stuck agent can't burn unbounded calls/time. Disable with CONTAINER_HOST_RUNAWAY_MAX=0; optional hard ceilings via CONTAINER_HOST_MAX_TOOL_CALLS / CONTAINER_HOST_MAX_TOOL_SECONDS.
Undo recording — reversible writes record an inverse descriptor built from the fetched before-state.
Risk tier — a descriptive label on the audit row derived from risk_level; it gates nothing.

Scope

This is the container-host member of the AIops-tools family (governed AI-ops with audit + budget + undo), for single-host Docker / Portainer / Podman. 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 + Podman (libpod) APIs. Missing a call, or want another container host family? Open an issue or PR — contributions welcome.

Verification status

Docker — exercised against a live Docker Engine 27.5.1 daemon: doctor and overview connected over the local socket, the restart-loop and image/volume bloat analyses were run against real crash-looping containers and real reclaimable data, and a governed stop_container wrote a row to the audit DB and recorded a working undo descriptor.
Portainer and Podman — mock-validated only. Those API paths are modelled from each project's public API shape and have not been exercised against a live server.
The full checklist — what the mock suite guarantees, what the Docker run already satisfied, and what a Portainer/Podman run still has to prove — is in docs/VERIFICATION.md. container-host-aiops doctor is the fastest live check on any platfor

Only the beginning is shown; read the rest in the repo

Container Host AIops

What it does

Install

Install Python (uv)

Open the Claude desktop app’s settings file

Paste these settings and save the file

Quit Claude and open it again

Try it

What you can do instead

Install Python (uv)

Open Terminal

Paste this command and press Enter

Type /mcp in Claude Code

Try it

Install Python (uv)

Click this button to open Cursor

Open the AI chat in Cursor in Agent mode

Try it

Install Python (uv)

Click this button to open VS Code

Open the AI chat in VS Code in Agent mode

Try it

Installed on your computer

At a glance

Which apps can use it

Related guides

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Discussion

User reviews

Compared with others in Developer toolsi

Common questions

Others in the same category

REA

GitHub

Serena MCP: the IDE for your agent

README from the maker

Container Host AIops

What it does

What works

What this tool does, and does not, decide

Capability matrix (38 MCP tools)

Platform support matrix

Quick start

As a Claude Code plugin

As an OpenClaw plugin

As a CLI or standalone MCP server

Governance

Scope

Missing a capability?

Verification status