Governed AI-ops for self-managed GitLab + Gitea CI/CD: pipelines, jobs, runners, artifacts, repo hyg
- ✓Open-source license (MIT)
- ✓Actively maintained (<30d)
- ✓Clear description
- ✓Documented (README)
/plugin marketplace add AIops-tools/CICD-AIops
/plugin install cicd-aiopsPlugins overview
<!-- mcp-name: io.github.AIops-tools/cicd-aiops -->
# CICD AIops
**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`](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](skills/cicd-aiops/references/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](https://docs.astral.sh/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 a CLI or standalone MCP server
```bash
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:
```bash
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
| Surface | GitLab (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, result, 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).
```json
{
"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):
```yaml
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
```bash
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.
What people ask about CICD-AIops
What is AIops-tools/CICD-AIops?
+
AIops-tools/CICD-AIops is plugins for the Claude AI ecosystem. Governed AI-ops for self-managed GitLab + Gitea CI/CD: pipelines, jobs, runners, artifacts, repo hyg It has 0 GitHub stars and its last recorded update is dated 2026-09-12.
How do I install CICD-AIops?
+
You can install CICD-AIops by cloning the repository (https://github.com/AIops-tools/CICD-AIops) or following the README instructions on GitHub. ClaudeWave also provides quick install blocks on this page.
Is AIops-tools/CICD-AIops safe to use?
+
Our security agent has analyzed AIops-tools/CICD-AIops and assigned a Trust Score of 87/100 (tier: Trusted). See the full breakdown of passed checks and flags on this page.
Who maintains AIops-tools/CICD-AIops?
+
AIops-tools/CICD-AIops is maintained by AIops-tools. The last recorded GitHub activity is dated 2026-09-12, with 0 open issues.
Are there alternatives to CICD-AIops?
+
Yes. On ClaudeWave you can browse similar plugins at /categories/plugins, sorted by popularity or recent activity.
Deploy CICD-AIops to your cloud
Ship this repo to production in minutes. Each platform spins up its own environment with editable env vars.
Maintain this repo? Add a badge to your README
Drop the badge into your GitHub README to show it's tracked on ClaudeWave. Each badge links back to this page and reflects the live Trust Score.
[](https://claudewave.com/repo/aiops-tools-cicd-aiops)<a href="https://claudewave.com/repo/aiops-tools-cicd-aiops"><img src="https://claudewave.com/api/badge/aiops-tools-cicd-aiops" alt="Featured on ClaudeWave: AIops-tools/CICD-AIops" width="320" height="64" /></a>More Plugins
Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands.
AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary
Academic Research Skills for Claude Code: research → write → review → revise → finalize
Agent skill that removes signs of AI-generated writing from text
A skill to stop your coding agent from burying the answer. ADHD-friendly output.
Create beautiful slides on the web using a coding agent's frontend skills