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alexpota/cloudscope-mcp

by Various

Multi-cloud cost management MCP server (Azure + GCP). Read-only access to spending, anomalies, forecasts, budgets, and guided FinOps workflows. Ask your AI about your cloud bill.

A

MCP

alexpota/cloudscope-mcp

Added 1 June 2026

#anomaly-detection #azure #azure-advisor #bigquery #budget-monitoring #claude #claude-code #cloud-billing

Overview

CloudScope is an MCP server that provides read-only access to multi-cloud cost data from Azure and GCP. It enables AI assistants to query spending, anomalies, forecasts, budgets, and guided FinOps workflows. Built in TypeScript.

Best for

Best for
Developers who want AI-assisted read-only cost monitoring across Azure and GCP

Use cases

  • Query current cloud spending across Azure and GCP from an AI assistant
  • Detect cost anomalies and generate forecasts through natural language
  • Run guided FinOps workflows without write access to cloud resources

Notes

CloudScope is an MCP server that provides read-only access to multi-cloud cost data from Azure and GCP. It enables AI assistants to query spending, anomalies, forecasts, budgets, and guided FinOps workflows. Built in TypeScript.

0 stars on GitHub. Last updated 2026-06-01. Licensed MIT.

Use cases

  • Query current cloud spending across Azure and GCP from an AI assistant
  • Detect cost anomalies and generate forecasts through natural language
  • Run guided FinOps workflows without write access to cloud resources

Pros

  • Read-only design prevents accidental cost changes or resource modifications
  • Covers both Azure and GCP in a single server
  • Integrates with any MCP-compatible AI client

Cons

  • No support for AWS cloud cost data
  • Zero stars on GitHub suggests limited community validation or early stage
  • Requires manual setup of cloud credentials and MCP client configuration

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Read-only design prevents accidental cost changes or resource modifications
  • Covers both Azure and GCP in a single server
  • Integrates with any MCP-compatible AI client

Cons

  • No support for AWS cloud cost data
  • Zero stars on GitHub suggests limited community validation or early stage
  • Requires manual setup of cloud credentials and MCP client configuration
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