GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者による説明(英語の原文)
Cloud DevOps analysis with guarded Git, infrastructure, cloud and observability operations.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"cloud-devops": {
"command": "npx",
"args": [
"-y",
"cloud-devops-mcp-server"
]
}
}
}ターミナルでこれを実行します
claude mcp add cloud-devops -- npx -y cloud-devops-mcp-serverプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"cloud-devops": {
"command": "npx",
"args": [
"-y",
"cloud-devops-mcp-server"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"cloud-devops": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"cloud-devops-mcp-server"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月6日にチェック
レジストリ名は、リポジトリを所有するGitHubアカウント alexcgodwin で確認済みです
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち1項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.14.0)がレジストリに届いたのは35 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにNode.jsも必要です。
同じカテゴリには:GitHub, Desktop Commander, Cloudflare MCP
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日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
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
Cloud DevOps MCP Server is a Model Context Protocol v2 server by Alex C. Godwin. It provides evidence-backed Cloud DevOps analysis across infrastructure, identity, Kubernetes, CI/CD, SRE and software supply-chain controls.
The v0.14 line adds an opt-in OpsChugex change-intelligence and blast-radius gateway. The public MCP forwards bounded planned-change, topology and readiness evidence to a host-configured private OpsChugex service and returns change risk, impacted topology nodes, representative blast paths, blockers, warnings and evidence gaps. Proprietary dependency propagation, risk weighting and blocker rules are not included in this public MIT repository.
The v0.13 line adds an opt-in OpsChugex advanced FinOps gateway. The public MCP forwards bounded cloud-cost, utilization and Kubernetes allocation evidence to a host-configured private OpsChugex service and returns optimization opportunities, cost anomalies, low/high savings ranges, confidence, cost correlations and evidence gaps. Proprietary savings factors, anomaly thresholds, prioritization and deduplication are not included in this public MIT repository.
The v0.12 line adds an opt-in OpsChugex cloud security posture gateway. The public MCP forwards bounded cloud asset, identity, secret and network-reachability evidence to a host-configured private OpsChugex service and returns security score, risk level, ordered findings, attack paths, evidence gaps and recommendations. Proprietary security rules, severity thresholds, scoring and attack-path correlation are not included in this public MIT repository.
The v0.11 line adds an opt-in OpsChugex policy and governance gateway. The public MCP sends bounded resource evidence and approved exception metadata to a host-configured private OpsChugex service and returns pass, review or block decisions with control findings and evidence gaps. Proprietary profiles, rules, weights and exception-processing logic are not included in this public MIT repository.
The v0.10 line adds an opt-in OpsChugex root-cause intelligence gateway. The public MCP sends bounded incident evidence to a host-configured private OpsChugex service and returns evidence-ranked probable causes, contradictions, limitations and next checks. Proprietary ranking and correlation rules are not included in this public MIT repository.
The v0.9 line adds an opt-in distributed-tracing and SLO-intelligence plane for Grafana Tempo and Jaeger v3 trace reads, service dependency mapping, tracing coverage assessment, multi-window SLO burn-rate analysis and trace/SLO incident correlation. The v0.8 production-observability and operations-intelligence plane remains available for Prometheus, Grafana, CloudWatch Logs Insights, Kubernetes health, GitHub Actions diagnosis, cloud health, FinOps and drift. Live AWS, Azure and GCP access remains bounded and read-only. Cloud mutation remains intentionally unavailable.
AI assistants are more useful in engineering work when they can call focused tools with clear inputs and consistent outputs. This server provides a Cloud DevOps tool layer for:
| Tool | Purpose |
|---|---|
assess_cloud_change_bundle | Correlates Terraform, IAM, Kubernetes and GitHub Actions evidence into one deployment-risk assessment with cross-domain change paths. |
assess_terraform_change | Scores Terraform/IaC risk and can derive evidence from raw Terraform plan JSON. |
build_incident_runbook | Produces a practical incident response runbook for a service, symptom, environment and severity. |
review_cicd_pipeline | Reviews CI/CD maturity while separating failed controls from unknown evidence. |
estimate_slo_error_budget | Calculates downtime and request-failure budgets with consistency validation. |
review_iam_policy | Parses IAM policy JSON and detects wildcard scope and privilege-escalation paths. |
review_kubernetes_deployment | Parses Kubernetes YAML for probes, resources, disruption protection, image and exposure risks. |
review_github_actions_workflow | Parses workflow YAML for triggers, immutable action pins, permissions, caching and concurrency. |
review_cloud_identity_policy | Applies AWS IAM, Azure RBAC or GCP IAM policy packs to raw policy JSON. |
review_terraform_security | Reviews Terraform plan JSON for destructive changes, public exposure, encryption, deletion protection and wildcard IAM. |
review_kubernetes_security | Reviews privileged mode, host access, service accounts, capabilities, seccomp, root filesystems and NetworkPolicy. |
review_software_supply_chain | Correlates CycloneDX/SPDX SBOM quality with CI action pinning, image immutability, signatures and provenance. |
When explicitly enabled, six additional tools provide allowlisted AWS/Azure/GCP identity verification, bounded inventory, managed Kubernetes discovery, observability configuration summaries, FinOps waste signals and drift reporting. No cloud mutation commands are exposed. AWS general inventory is sourced from the Resource Groups Tagging API, so untagged AWS resources may not appear in that inventory or AWS drift comparison.
When explicitly enabled, twelve additional tools provide bounded Prometheus queries, Grafana alert summaries, CloudWatch Logs Insights queries, Kubernetes pod-health summaries, GitHub Actions failure diagnosis, cross-signal incident correlation, cloud-health assessment, deployment/incident correlation, observability coverage assessment, FinOps correlation, cross-runtime drift analysis and operations briefs. Endpoints, cloud scopes, log groups, cluster contexts, namespaces and repositories are allowlisted. The layer is read-only and exposes no alert mutation, deployment mutation or arbitrary shell execution.
When explicitly enabled, six additional v0.9 tools provide bounded Tempo/Jaeger trace search and retrieval, service dependency mapping, tracing coverage assessment, multi-window SLO burn-rate analysis and trace/SLO incident correlation. Remote tracing endpoints must be allowlisted and use HTTPS unless loopback. Backend credentials stay in host environment variables. Trace search windows and result sizes are bounded, and the plane exposes no trace ingestion, sampling mutation or telemetry deletion.
When explicitly enabled, v0.10 exposes diagnose_root_cause. The tool accepts bounded evidence from metrics, logs, traces, Kubernetes, cloud, Terraform and CI/CD, then calls a host-configured private OpsChugex service. The public MCP contains no proprietary ranking rules, accepts no service URL or credential as tool input, and performs no remediation. Evidence scores represent evidence strength rather than statistical probability.
When explicitly enabled, v0.11 exposes assess_governance_policy. The tool accepts bounded factual resource evidence plus optional owner-attributed, time-bounded exceptions and forwards them to the private OpsChugex policy engine. It returns pass, review, or block with control findings and evidence gaps.
The public MCP contains no proprietary governance profiles, policy rules, scoring weights, exception evaluation logic or enforcement capability. The service URL and token remain host-side and cannot be supplied as MCP arguments.
When explicitly enabled, v0.12 exposes assess_cloud_security_posture. The tool accepts bounded asset, identity, secret and network-reachability evidence and forwards it to the private OpsChugex security engine. It returns a security score, risk level, ordered findings, correlated attack paths, evidence gaps and recommended next actions.
The public MCP contains no proprietary security detection thresholds, severity rules, scoring logic or attack-path algorithm. It cannot rotate credentials, change IAM, modify network controls, alter encryption settings or remediate infrastructure.
When explicitly enabled, v0.13 exposes analyze_advanced_finops. The tool accepts bounded cloud-cost, utilization and Kubernetes allocation evidence and forwards it to the private OpsChugex FinOps engine. It returns optimization opportunities, anomalies, savings ranges, confidence, cost correlations and evidence gaps.
The public MCP contains no proprietary savings factors, anomaly thresholds, prioritization rules, confidence algorithm or portfolio deduplication logic. It does not resize resources, terminate workloads, purchase commitments, change Kubernetes requests or perform billing actions.
When explicitly enabled, v0.14 exposes analyze_change_blast_radius. T
冒頭だけを表示しています。続きはリポジトリで読めます