GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
Beschreibung vom Entwickler (englisches Original)
Governed self-managed GitLab + Gitea CI/CD ops: pipelines, runners, artifacts, RCA. 28 tools.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Öffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"cicd-aiops": {
"command": "uvx",
"args": [
"cicd-aiops"
]
}
}
}Führe das in deinem Terminal aus
claude mcp add cicd-aiops -- uvx cicd-aiopsIn .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"cicd-aiops": {
"command": "uvx",
"args": [
"cicd-aiops"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"cicd-aiops": {
"type": "stdio",
"command": "uvx",
"args": [
"cicd-aiops"
]
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
Dieser Server läuft auf deinem Computer, und ChatGPT kann sich nur mit Servern im Internet verbinden. Wähle eine andere App.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
Diese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Läuft auf deinem Computer; die Tool-Liste erscheint nach der Installation in deiner KI-App.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto AIops-tools bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieser Server läuft auf deinem Computer; es gibt keinen Endpunkt im Internet
Läuft auf deinem Computer und nutzt stattdessen lokale Einstellungen
Läuft auf deinem Computer; Tool-Listen können wir nur von Endpunkten im Internet lesen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 1 von 1 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Die Registry nennt keinen erforderlichen Schlüssel, manche Server bitten dich aber bei der ersten Nutzung, dich anzumelden.
Er läuft auf deinem Computer. Deine KI-App startet ihn bei Bedarf, und die Daten laufen nicht über die Server des Entwicklers (außer der Server ruft selbst einen Onlinedienst auf).
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (0.14.0) kam vor 8 Tagen in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Außerdem brauchst du Python (uv) auf deinem Computer.
In derselben Kategorie: GitHub, Desktop Commander, Cloudflare MCP
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
Cloudflare MCP servers
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
Audit availability: Real writes require a committed
pendingaudit 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 doctoris 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).
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.
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.
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.
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.
| 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.
delete_artifacts --dry-run.All four are transparent heuristics: thresholds are named parameters and every flag carries its numbers.
Every MCP tool and every CLI write runs through the vendored harness in cicd_aiops/governance/. It records; it does not authorize (see above).
~/.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.CICD_RUNAWAY_MAX=0; optional hard ceilings via CICD_MAX_TOOL_CALLS / CICD_MAX_TOOL_SECONDS.~/.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_level (reads low; mutating writes medium; delete_artifacts high); it gates nothing.dry_run=True (MCP) / --dry-run (CLI) and previews without calling the server.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).
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_BYaudit annotation) must be set in theenvblock
above, not in
~/.zshrc.
Alternatively: cicd-aiops mcp (same server, CLI entry point).
~/.cicd-aiops/config.yaml (the wizard writes this):
targets:
The token for each target is stored encrypted under the target's name. Relocate all state (config, audit, undo, secrets) with CICD_AIOPS_HOME.
uv sync
uv run pytest -q uv run ruff check .
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.
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.