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Opencloudcosts Mcp

@x7even

Opencloudcosts Mcp について

Anchor AI FinOps to real, live cloud pricing. Multi-cloud MCP server for AWS, GCP & Azure — public list prices and enterprise negotiated rates (Reserved Instances, Savings Plans, CUDs, EDPs). No credentials needed to get started.

基本情報

カテゴリ

クラウドとインフラ

トランスポート

stdio

公開者

x7even

投稿者

Xin S

設定

以下の設定を使って、このサーバーを MCP 対応クライアントに追加してください。

{
  "mcpServers": {
    "cloudcost": {
      "command": "opencloudcosts",
      "env": {
        "OCC_GCP_API_KEY": "your-gcp-api-key",
        "AWS_ACCESS_KEY_ID": "your-aws-key-id",
        "AWS_SECRET_ACCESS_KEY": "your-aws-secret",
        "OCC_AWS_ENABLE_COST_EXPLORER": "true",
        "OCC_GCP_BILLING_ACCOUNT_ID": "012345-567890-ABCDEF"
      }
    }
  }
}

ツール

ツールは検出されませんでした

ツールは README から自動的に抽出されます。メンテナーは ## Tools という見出しの下に記載することで、このタブに反映できます。

概要

What is Opencloudcosts Mcp?

Opencloudcosts Mcp is an MCP server that gives AI assistants live, structured access to AWS, GCP, and Azure pricing via 16 tools. It replaces static training data with real-time provider API calls, enabling accurate, account-specific cost answers for multi-cloud workloads.

How to use Opencloudcosts Mcp?

Install via PyPI or download a GitHub release binary, configure the required environment variables for credential-based access (e.g., OCC_GCP_API_KEY, OCC_AWS_ENABLE_COST_EXPLORER), and connect the server to your MCP-capable AI assistant. The model then calls any of the 16 tools to retrieve pricing, compare clouds, or estimate unit economics.

Key features of Opencloudcosts Mcp

  • 16 MCP tools for pricing, FinOps, discovery, and cache management
  • Live pricing from AWS, GCP, and Azure provider APIs (not training data)
  • Multi-cloud BOM comparison with 8 concurrent provider calls
  • Multi-region fan-out with up to 32 goroutines
  • Effective/contracted rate support (RI, SP, EDP, CUD) where credentials are provided
  • HTTP service mode with bearer auth, rate limiting, and Kubernetes-ready probes

Use cases of Opencloudcosts Mcp

  • Compare a full multi-resource workload across AWS, GCP, and Azure simultaneously
  • Find the cheapest region for a given instance type across all available regions
  • Estimate unit economics (cost per user, per request) for a planned architecture
  • Retrieve post-discount effective rates from Reserved Instances or Savings Plans
  • Get a structured bill of materials (BOM) estimate on-demand vs. committed terms

コメント

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