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chaandannn/finopsmcp

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The open-source AI-native FinOps platform. Ask nable about your AWS, Azure, GCP, Kubernetes, and SaaS spend inside Claude or Cursor. Runs on your machine; credentials never leave i

C

MCP

chaandannn/finopsmcp

Added 13 July 2026

#ai #anomaly-detection #aws #azure #claude #claude-desktop #cloud-cost #cost

Overview

An open-source FinOps platform that lets you query cloud and SaaS spending across AWS, Azure, GCP, Kubernetes, and other services directly from Claude or Cursor. It runs locally on your machine so credentials never leave your environment.

Best for

Best for
Developers and FinOps practitioners who want to query cloud costs from within their AI coding assistant

Use cases

  • Ask natural language questions about cloud cost data inside Claude or Cursor
  • Query multi-cloud and Kubernetes spending without leaving your coding assistant
  • Audit SaaS expenses across providers from a single local interface

How to use

Install

uvx nable

Tools exposed

  • uv
  • pip

Tested with

Claude Desktop, Claude Code, Cursor, Windsurf, VS Code

Example client config

{\n  "mcpServers": {\n    "nable": { "command": "uvx", "args": ["--python", "3.12", "finops-mcp"] }\n  }\n}

Notes

An open-source FinOps platform that lets you query cloud and SaaS spending across AWS, Azure, GCP, Kubernetes, and other services directly from Claude or Cursor. It runs locally on your machine so credentials never leave your environment.

8 stars on GitHub. Last updated 2026-07-13. Licensed Apache-2.0.

Use cases

  • Ask natural language questions about cloud cost data inside Claude or Cursor
  • Query multi-cloud and Kubernetes spending without leaving your coding assistant
  • Audit SaaS expenses across providers from a single local interface

Pros

  • Runs entirely on your machine, keeping credentials secure
  • Supports major cloud providers plus Kubernetes and SaaS
  • Integrates directly with Claude and Cursor for in-editor queries

Cons

  • Requires local setup and Python environment
  • Limited to querying data you have already configured access to
  • No built-in visualization or reporting beyond text responses

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

Pros

  • Runs entirely on your machine, keeping credentials secure
  • Supports major cloud providers plus Kubernetes and SaaS
  • Integrates directly with Claude and Cursor for in-editor queries

Cons

  • Requires local setup and Python environment
  • Limited to querying data you have already configured access to
  • No built-in visualization or reporting beyond text responses

Pairs with

Other entries in the index that connect to this one. Click through to see the chain.

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