Cicd Aiops
Governed self-managed GitLab + Gitea CI/CD ops: pipelines, runners, artifacts, RCA. 28 tools.
- Transport
- Not stated
- Package
- —
- Registry id
- io.github.AIops-tools/cicd-aiops
No install snippet on purpose. A working MCP config is a command, its arguments and an environment block — the last two are where API keys live, so this catalogue never stores them and cannot publish them. Follow the link above for the authors' own instructions.
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 doctoris the fastest live check — seedocs/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:
From the project's README.