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CICD AIops

by AIops-toolsversion 0.14.0i★ –iRuns on your computer
Registry nameio.github.AIops-tools/cicd-aiops

Install

Overview

Description from the maker (original English)

Governed self-managed GitLab + Gitea CI/CD ops: pipelines, runners, artifacts, RCA. 28 tools.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Developer tools

Install

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

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • The registry lists no key to fill in.

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

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

Run this in your terminal

claude mcp add cicd-aiops -- uvx cicd-aiops

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

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

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

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

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 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account AIops-tools, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – 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

Compared with others in Developer toolsi

  • More stars than 0% of the other 1395 servers in this category
  • Published to the registry more recently than 83% of the other 1395 servers in this category
  • Basic checks equal to or better than 100% of the other 1395 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 CICD AIops safe?

It passed 1 of 1 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 –, and the latest version (0.14.0) reached the registry 8 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: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

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

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

GitHub

by github

GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

Computer or cloud★ 34,245MITUpdated 4 days ago
Install

Desktop Commander

by wonderwhy-er

MCP server for terminal commands, file operations, and process management

Runs on your computer★ 10,225MITUpdated 16 days ago
Install

Cloudflare MCP

by cloudflare

Cloudflare MCP servers

Runs in the cloud★ 4,446Apache-2.0Updated 14 months ago
Install

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.

CICD 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.

Governed AI-ops for self-managed GitLab and self-hosted Gitea.

cicd-aiops is for the team running its *own* CI/CD forge — a GitLab instance or a Gitea server on your hardware, in your lab, behind your VPN — who want an AI agent that can answer "why did the pipeline fail?", "which runner is wedged?", "where did 40 GB of artifact storage go?" and "what work went stale?" and then act (retry, cancel, pause, delete, protect) only through an audited, budgeted, risk-tiered, undo-recorded governance harness. It is not a SaaS integration: it speaks the GitLab REST API v4 and the Gitea API v1 directly against your server, with credentials encrypted at rest.

Verification status: modelled from each project's public API docs and

exercised against mocked HTTP responses; there is no recorded end-to-end run

against a live server yet. cicd-aiops doctor is the fastest live check —

see docs/VERIFICATION.md.

Routing: Do NOT use this for Kubernetes deploy state — use k8s-aiops.

This tool ends at the CI/CD server's API (pipelines, runners, artifacts,

repo hygiene).

What this tool does, and does not, decide

It delivers CI/CD 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 token you connect it with: give it a GitLab/Gitea access token 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 ~/.cicd-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.

Running a smaller / local model? See agent-guardrails.md — it lists the guardrails this tool enforces for you (so you don't spend prompt budget restating them) and gives a ready-made system prompt for what's left.

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 cicd-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 cicd-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/cicd-aiops

openclaw skills info cicd-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 cicd-aiops        # or: pip install cicd-aiops

cicd-aiops init # wizard: base URL + token (encrypted) + TLS verify cicd-aiops doctor # connectivity + token-scope probe per target cicd-aiops overview # version, identity, projects, runners at a glance

Then the interesting parts:

cicd-aiops rca pipelines dev/api        # classify recent failed pipelines

cicd-aiops rca runners # offline/stale runners, tag saturation cicd-aiops rca storage # artifact/repo bloat, reclaimable bytes cicd-aiops rca stale dev/api # stale MRs/branches, protection gaps

cicd-aiops pipelines retry dev/api 42 --dry-run cicd-aiops artifacts delete dev/api --older-than-days 30 --dry-run

Every write has --dry-run and a double confirmation, and executes through the same governed path the MCP tools use — so CLI writes are audited too.

Support scope

SurfaceGitLab (REST v4, self-managed)Gitea (API v1, self-hosted)
Server version + token identity✅✅
Projects + storage statistics✅ (statistics=true)✅ (repo size)
Pipelines / runs, jobs, trace tails✅✅ (Actions runs/jobs/logs)
Runner fleet (list/detail)✅❌ teaching error (no API v1 equivalent)
Merge/pull requests, branches, protection, releases✅✅
Artifact inventory✅ (via jobs)✅ (Actions artifacts)
retry_pipeline / cancel_pipeline✅❌ teaching error
pause_runner / resume_runner✅❌ teaching error
delete_artifacts✅❌ teaching error
update_branch_protection✅✅

Where a platform lacks a surface, the platform registry raises a *teaching error* naming the resources that are available — the agent learns instead of hitting a mystery 404. GitLab.com / Gitea Cloud SaaS accounts are out of scope by design: this tool targets self-managed instances.

Flagship analyses (the reason this tool exists)

  1. `pipeline_failure_rca` — pulls recent failed pipelines with failed-job trace tails and classifies each failure: *test-failure / dependency-network / runner-timeout / oom / script-error*, with the matched evidence, a cause, and an action per pipeline.
  2. `runner_health_rca` — offline/stale/paused runners (contact-age threshold), jobs queued past a threshold, and per-tag saturation (queued jobs vs online runners).
  3. `artifact_storage_bloat_analysis` — projects ranked by repo + artifact bytes, expired-but-kept artifacts, and a reclaimable-bytes estimate that feeds straight into delete_artifacts --dry-run.
  4. `stale_work_audit` — merge/pull requests idle past N days, branches with no commits for N days, and protection gaps (unprotected default branch, force-push allowed).

All four are transparent heuristics: thresholds are named parameters and every flag carries its numbers.

Governance (built in, always on)

Every MCP tool and every CLI write runs through the vendored harness in cicd_aiops/governance/. 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 ~/.cicd-aiops/audit.db (relocatable via CICD_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 CICD_RUNAWAY_MAX=0; optional hard ceilings via CICD_MAX_TOOL_CALLS / CICD_MAX_TOOL_SECONDS.
  • Undo — reversible writes record a replayable inverse in ~/.cicd-aiops/undo.db, built from the *fetched* before-state: pause_runner ⇄ resume_runner, and update_branch_protection replays the prior settings. Irreversible writes (retry_pipeline, cancel_pipeline, delete_artifacts) record priorState (status / bytes+count) instead.
  • Risk tier — a descriptive label on the audit row derived from risk_level (reads low; mutating writes medium; delete_artifacts high); it gates nothing.
  • Dry-run everywhere — every write takes dry_run=True (MCP) / --dry-run (CLI) and previews without calling the server.
  • Sanitize — all server-returned text is folded through an injection-safe normaliser (bounded strings, capped depth) before an agent sees it; all path parameters are percent-encoded so an identifier can never rewrite a URL.
Secrets

Tokens live in ~/.cicd-aiops/secrets.enc — Fernet-encrypted, key derived from a master password via scrypt. Never plaintext on disk. Set CICD_AIOPS_MASTER_PASSWORD for non-interactive/MCP use, and manage with cicd-aiops secret set|list|remove|migrate. TLS verification defaults ON (the init wizard asks before turning it off for lab certs).

MCP server

26 governed tools (20 reads incl. the four flagship analyses, 6 writes).

{

"mcpServers": { "cicd-aiops": { "command": "uvx", "args": ["--from", "cicd-aiops", "cicd-aiops-mcp"], "env": { "CICD_AIOPS_MASTER_PASSWORD": "your-master-password" } } } }

Env-block caveat: MCP clients launch the server with a *minimal*

environment — your shell profile is not sourced. Anything the server needs

(CICD_AIOPS_MASTER_PASSWORD, CICD_AIOPS_HOME, and any optional

CICD_AUDIT_APPROVED_BY audit annotation) must be set in the env block

above, not in ~/.zshrc.

Alternatively: cicd-aiops mcp (same server, CLI entry point).

Configuration

~/.cicd-aiops/config.yaml (the wizard writes this):

targets:
  • name: gl1 platform: gitlab # or: gitea base_url: https://git.example.com verify_ssl: true # default ON; set false only for lab certs

The token for each target is stored encrypted under the target's name. Relocate all state (config, audit, undo, secrets) with CICD_AIOPS_HOME.

Development

uv sync

uv run pytest -q uv run ruff check .

缺功能?

缺功能提 issue/PR 欢迎留言 — if a GitLab/Gitea surface you need is missing (runner administration on newer Gitea, per-job retry, scheduled pipelines, group-level rollups…), open an issue or PR at https://github.com/AIops-tools/CICD-AIops. The platform registry is designed so a new resource is one path-map entry, not a refactor.

License

MIT. GitLab is a trademark of GitLab Inc.; Gitea is a trademark of its project owners. This project is independent and not affiliated with either.

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