GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Governed self-managed GitLab + Gitea CI/CD ops: pipelines, runners, artifacts, RCA. 28 tools.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"cicd-aiops": {
"command": "uvx",
"args": [
"cicd-aiops"
]
}
}
}在终端中运行这条命令
claude mcp add cicd-aiops -- uvx cicd-aiops粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"cicd-aiops": {
"command": "uvx",
"args": [
"cicd-aiops"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"cicd-aiops": {
"type": "stdio",
"command": "uvx",
"args": [
"cicd-aiops"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 AIops-tools 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.14.0)于8天前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
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
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
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.