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作者による説明(英語の原文)
Cloud cost + FinOps knowledge for AI agents: AWS/Azure/GCP optimisation, AI spend, waste playbooks.
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。
ウェブ、デスクトップ、モバイルのClaudeで使えます:
https://mcp.optimnow.io/mcpClaude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"cloud-finops": {
"command": "uvx",
"args": [
"cloud-finops-mcp"
]
}
}
}ターミナルでこれを実行します
claude mcp add --transport http cloud-finops https://mcp.optimnow.io/mcpclaude mcp add cloud-finops -- uvx cloud-finops-mcp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-finops": {
"url": "https://mcp.optimnow.io/mcp"
}
}
}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-finops": {
"command": "uvx",
"args": [
"cloud-finops-mcp"
]
}
}
}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-finops": {
"type": "http",
"url": "https://mcp.optimnow.io/mcp"
}
}
}プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"cloud-finops": {
"type": "stdio",
"command": "uvx",
"args": [
"cloud-finops-mcp"
]
}
}
}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。
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:
https://mcp.optimnow.io/mcpメニューの名前は、プランや時期によって少し違うことがあります。
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。
ツールの名前と説明は、サーバーが2026年11月6日に返したそのままの内容です。書いたのは作者で、私たちではありません。プレーンテキストとして表示しています。
list_referencesSee what FinOps guidance is available: billing mechanics, commitment strategy, allocation and chargeback, AI cost management, and per-provider cost handbooks (AWS, Azure, GCP, OCI, Databricks, Snowflake, ...). Use this to discover what the library covers before deciding what to f
get_referenceFetch the guidance on one FinOps topic - the billing mechanics, decision rules and worked examples behind a defensible answer - either whole or one section at a time. Use this when you need the actual content of one known reference, after ``list_references`` or ``find_references`
find_referencesFind which guidance serves a FinOps question - how to commit, size, allocate, charge back, forecast, or govern cloud and AI spend. Use this for questions like "how should we size Savings Plans", "what should Finance own in chargeback", "what does a Crawl-stage org tackle first" -
list_playbooksSee every ready-made runbook for finding and fixing cloud waste: idle, orphaned and overprovisioned resources, egress surprises, schedule blindness and AI/ML inefficiency across AWS, Azure and GCP. Use this to discover which waste patterns have a runbook. When the question alread
get_playbookFetch the step-by-step runbook for one specific waste pattern: symptoms, the detection queries to run, the fix, and the anti-pattern to avoid. Use this when the user asks how to detect, confirm, or fix one specific named waste pattern (zombie NAT gateway, snapshot sprawl, idle Sa
find_playbooksFinds the runbook for a specific cloud waste pattern, filtered by provider, service, waste category or detection confidence. Useful before answering a specific waste or cost-fix question: each runbook includes a tested detection query the user can run in their own account, so it
get_live_figuresGet the current value of a figure a reference quotes with a date. Use this when a reference quotes a figure from an OptimToken guide ("measured on the 2026-10-25 OptimToken catalogue") and the answer needs the current value: the Compute Savings Plan or reservation discount, the g
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 OptimNow 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
174ミリ秒で応答(HTTP 200)
サインイン不要
7件のツールの説明を読み、AIへの隠れた指示は見つかりませんでした
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3項目のうち3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。
どちらでも使えます。パソコンにインストールしても、クラウド版につないでもかまいません。
GitHubリポジトリの最終更新は–、最新バージョン(1.47.0)がレジストリに届いたのは昨日です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。URLでつながるので、リモートMCPサーバーに対応したアプリ(開発者モードのChatGPTなど)でも使えます。
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。
FinOps knowledge for AI assistants: billing mechanics, commitment decisions and waste runbooks for AWS, Azure, GCP, AI and data platforms. By OptimNow.
Ask your assistant how to reduce a cloud bill, size a commitment, read a term sheet or allocate shared AI costs, and it answers from how billing works, with decision rules and worked examples, instead of general advice. The same files work in Claude, ChatGPT, Gemini, Cursor and any MCP-compatible tool. Open source, written by OptimNow from enterprise FinOps delivery, and aligned with the FinOps Foundation framework.
Each question below is answered by a file that exists in this repository today.
FinOps lead
Finance and procurement
Engineering and platform
AI product owner
Neither the skill nor the connector can see your cloud account. For a question about your own resources, the answer is a detection query you run yourself, taken from the matching runbook.
The reference library is mapped to the 22 capabilities of the FinOps Foundation framework, grouped in its 4 domains. A filled square means at least one reference owns the capability; a grey square means the capability is covered inside another file; a dashed square is a known gap, listed with its reasoning in docs/ROADMAP.md.
This map is generated from the frontmatter of every reference file, and the CI pipeline fails when the committed map no longer matches the files (fcp-coverage.md).
The matrix reads the library by business need. Every cell comes from a named reference file, listed in the notes under the tables.
| Level | Meaning |
|---|---|
| ● deep | A dedicated reference or section, with decision rules, worked examples or detection queries |
| ◐ partial | Covered inside a broader file, or mechanics only |
| – | Not covered today |
| n/a | The combination does not exist |
Hyperscalers
| Business need | AWS | Azure | GCP |
|---|---|---|---|
| Understand and allocate the bill | ● | ● | ● |
| Budget and forecast | ● | ● | ● |
| Commitments and discounts | ● | ● | ● |
| Contract negotiation and renewal | ● | ● | ● |
| Reduce waste | ● | ● | ● |
| AI and GenAI spend | ● | ● | ● |
| Data platforms | ◐ | ● | ◐ |
| SaaS and licences | ◐ | ◐ | ◐ |
| Carbon footprint | ● | ◐ | ◐ |
Other estates
| Business need | OCI | On-prem |
|---|---|---|
| Understand and allocate the bill | ◐ | ● |
| Budget and forecast | ◐ | ◐ |
| Commitments and discounts | ◐ | ◐ |
| Contract negotiation and renewal | – | – |
| Reduce waste | ◐ | ◐ |
| AI and GenAI spend | – | ◐ |
| Data platforms | – | – |
| SaaS and licences | – | ◐ |
| Carbon footprint | – | – |
Platforms
| Business need | AI | Data | SaaS |
|---|---|---|---|
| Understand and allocate the bill | ● | ● | ◐ |
| Budget and forecast | ● | ◐ | ◐ |
| Commitments and discounts | ● | ● | ◐ |
| Contract negotiation and renewal | – | ◐ | ◐ |
| Reduce waste | ● | ● | ● |
| AI and GenAI spend | ● | ◐ | ● |
| Data platforms | n/a | ● | n/a |
| SaaS and licences | ◐ | ◐ | ● |
| Carbon footprint | – | – | – |
On-prem covers owned data centres and the hybrid platforms (Outposts, Azure Local, Arc). AI covers the AI platforms: Anthropic, AWS Bedrock, Azure OpenAI, GCP Vertex AI and the open-weight vendor APIs. Data covers Databricks, Snowflake and Microsoft Fabric. SaaS covers SaaS applications, AI coding tools and licences.
Where each cell comes from
All paths are under plugins/cloud-finops/skills/cloud-finops/.
references/finops-aws-billing.md, finops-allocation-showback.md, finops-focus.md, finops-tagging.md. Azure: finops-azure-billing.md, finops-focus.md, finops-tagging.md. GCP: finops-gcp.md (cost data foundation), finops-focus.md, finops-kubernetes.md. OCI, partial: finops-oci.md (cost reports, cost-tracking tags), finops-focus.md. On-prem: finops-on-prem-hybrid.md (internal bill, usage ingestion). AI platforms: the "Cost visibility and allocation" sections of finops-bedrock.md, finops-azure-openai.md, finops-vertexai.md, finops-anthropic.md; finops-for-ai.md. Data platforms: finops-databricks.md (system tables, allocation), finops-fabric.md (shared-capacity allocation), finops-snowflake.md (query attribution). SaaS, partial: finops-sam.md (discovery), finops-focus.md (FOCUS for SaaS vendors), finops-ai-dev-tools.md (attribution patterns).finops-forecasting.md, finops-anomaly-management.md, and the Budgets sections of finops-aws-billing.md and finops-azure-billing.md. GCP: finops-gcp.md (budgets, spend caps), finops-anomaly-management.md. OCI, partial: finops-oci.md (Budgets). On-prem, partial: finops-on-prem-hybrid.md (rate setting); capacity planning is on the roadmap. AI platforms: finops-ai-value-management.md (AI investment budgets, stage gates), finops-forecasting.md (AI forecast scenarios), finops-anthropic.md (spend limits). Data platforms, partial: budget controls in finops-snowflake.md, finops-databricks.md, finops-fabric.md. SaaS, partial: finops-sam.md (renewal calendar, metrics), finops-ai-dev-tools.md (spending caps).finops-aws-commitments.md, finops-aws-patterns-databases.md (database commitment tree), playbooks/aws-expiring-commitment-no-decision.md. Azure: finops-azure-commitments.md, playbooks/azure-unused-reservation.md. GCP: finops-gcp.md (CUDs, BigQuery commitments), finops-vertexai.md (Flexible Savings Plans), playbooks/gcp-cud-mismatch.md. OCI, partial: finops-oci.md (Universal Credits). On-prem, partial: finops-on-prem-hybrid.md (hybrid platform terms: Outposts, Exadata Cloud@Customer). AI platforms: finops-genai-capacity.md, provisioned capacity in finops-azure-openai.md, finops-bedrock.md, finops-vertexai.md. Data platforms: finops-databricks.md (committed-use bands), finops-snowflake.md (capacity model), finops-fabric.md (reservation). SaaS, partial: finops-ai-dev-tools.md (plan tiers), finops-sam.md (multi-year agreements).finops-cloud-contracts.md, plus finops-azure-billing.md (EA-to-MCA). Data platforms, partial: the data platform section of finops-cloud-contracts.md, finops-databricks.md, finops-snowflake.md. SaaS, partial: finops-sam.md (renewal governance), finops-itam.md (pre-renewal checkpoint, joint negotiation). OCI, on-prem and AI platforms: no file. See "Contract negotiation and renewal" below.finops-aws.md, the 5 finops-aws-patterns-*.md files, 22 runbooks. Azure: finops-azure.md, finops-azure-patterns.md, 10 runbooks. GCP: the pattern catalogue inside finops-gcp.md, 7 runbooks. OCI, partial: finops-oci.md (6 patterns, no runbook). On-prem, partial: finops-on-prem-hybrid.md (idle capacity line, cost score). AI platforms: finops-for-ai.md (anti-patterns), finops-genai-capacity.md (provisioned-capacity waste), the optimisation sections of the 4 AI platform files, 2 cross-cloud runbooks. Data platforms: the pattern sections of finops-databricks.md, finops-snowflake.md, finops-fabric.md. SaaS: finops-sam.md (sprawl patterns), finops-ai-dev-tools.md (optimisation levers).finops-bedrock.md, finops-aws.md (SageMaker), the GPU and SageMaker runbooks. Azure: finops-azure-openai.md. GCP: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