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Health: ActiveRecent health check succeeded.Last checked 9/11/2026, 8:48:03 PM

Finopsmcp

User RatingsBe the first to rate and review this MCP server!
View Repository18 GitHub StarsTotal stargazers on GitHub for the source repository (18 stars).Visit Website
cloudfinopscost-managementlocalmcp

Local FinOps MCP server that analyzes cloud and AI bills, finds waste, and proposes fixes via pull requests.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to CursorAdd to VS Code
Automated check passed— started and listed 10 tools correctly (1mo ago).
Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "chaandannn-finopsmcp": {
      "command": "uvx",
      "args": [
        "nable"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Tool Schemas (10) Directory Badge Claim listing Alternatives☁️ More in Cloud Platforms

Overview

This MCP server aggregates cost data from AWS, Azure, GCP, Kubernetes, and 15+ SaaS and AI providers on your local machine in a read-only manner. It identifies cost waste such as idle resources and oversized instances, quantifies potential savings, and proposes fixes as pull requests for human approval. It integrates with Claude, Cursor, and VS Code to enable natural language cost queries and budget gating for AI agents without sending billing data off your device.

Use cases

•Aggregate cloud and AI spend across multiple providers locally
•Identify idle or oversized resources wasting money
•Generate pull requests to fix cost waste with human approval
•Query cost data interactively inside Claude or Cursor
•Implement budget gating for AI agents before cost-affecting actions

Key features

•Read-only local scanning of cloud and AI billing APIs
•Supports AWS, Azure, GCP, Kubernetes, and 15+ SaaS/AI providers
•Cost waste detection with dollar impact estimates
•Pull request generation for cost-saving fixes
•Natural language cost queries in Claude, Cursor, VS Code
•Pre-action budget gate for AI agents with policy checks

Capabilities & Tool Schemas (10) ~2.5k tokensApproximate context cost of this server’s tool schemas (~4 chars/token), before any tool is called. Actual usage depends on your client and model.Verified live Verified liveCaptured by calling this server’s live tools/list endpoint.

Inspect callable tools, capabilities, and parameters exposed to AI agents by Finopsmcp.

connect_aws

Connect an AWS account from inside your MCP client, no terminal needed. Propose-then-confirm and local-only. It reads AWS credentials that already exist on this machine (named profiles, environment, the default chain), verifies each against STS, and connects the one you choose. It never creates, modifies, or deletes anything in your AWS account, and credentials stay on this machine. Call it with no arguments first to see which accounts are available (nothing is stored). Then call it again with account_id set to the one to connect. Examples: - "Connect my AWS account" - "Use the credentials on this machine to connect AWS"

connect_azure

Guide connecting Azure while keeping the service-principal secret off the model. Azure has no local credentials nable can safely auto-detect, so connecting needs a client secret. Unlike connect_aws and connect_gcp (which read credentials already on the machine, so nothing sensitive passes through this conversation), an Azure secret would have to be pasted into the chat to reach a tool argument, which routes it through the model provider. nable does not do that. This tool returns the Cloud Shell script and has you finish the connect in your OWN terminal with `finops setup azure`, which encrypts the secret into your local vault. The model never sees the secret. Examples: - "Connect Azure" - "How do I connect my Azure subscription?"

get_cost_summary

Get total spend summarized by service, account, and region. Examples: - "How much did we spend last month?" - "Give me an AWS cost summary for January"

estimate_change_cost

Cost preflight for a proposed change: what it costs and whether it fits budget. Agent-native. Call this BEFORE applying an infrastructure change to get a machine verdict (ok / warn / over_budget / no_budget) plus the monthly and annual cost delta and the budget headroom. Read-only: it estimates and checks, it never applies anything. Describe the change one of these ways: - terraform_plan_json / terraform_plan_file / tf_dir : a Terraform plan - helm_diff : output of `helm diff upgrade` or a values.yaml diff - monthly_delta_usd : a known monthly cost delta (escape hatch for any change the estimators don't parse, e.g. "launch a db.r6g.4xlarge") budget_name selects which budget to check against; default is the first active budget. With no budget configured the verdict is "no_budget" and the cost delta is still returned. Good triggers: "will this fit my budget", "what will this terraform/helm change cost before I apply it", "cost preflight", "can the agent afford this change". Examples: - "What would this change cost per month?" - "Preflight the cost of this terraform plan"

connect_gcp

Connect a Google Cloud billing account from inside your MCP client, no terminal. Propose-then-confirm and local-only. It reads Google Cloud credentials that already exist on this machine (GOOGLE_APPLICATION_CREDENTIALS or gcloud Application Default Credentials), lists the open billing accounts they can see, and connects the one you choose. It never changes anything in GCP, and credentials stay on this machine. Call it with no arguments to see the billing accounts available (nothing is stored). Then call it again with billing_account_id set to connect one. Examples: - "Connect my Google Cloud billing" - "Use my gcloud login to connect GCP"

list_connected_providers

List every cloud, SaaS, and LLM provider nable knows, each marked connected or not-configured, plus the active plan. The starting point for "what am I connected to" and for spotting which connector still needs credentials (each not-configured entry names the setup command to run). Examples: - "Which providers are connected?" - "Is GCP set up yet?"

Documentation Overview

nable

See where your cloud and AI bills go, and spend less. Runs in your terminal or inside Claude, Cursor, and VS Code.

PyPI PyPI Downloads Tests License: Apache-2.0 MCP Toplist

You do not need to be a cloud-cost expert. nable does three things:

  • Shows what you spend across AWS, Azure, GCP, Kubernetes, and 15+ AI and SaaS providers, in one place.
  • Finds what you are wasting (idle servers, oversized databases, forgotten storage) and puts a dollar figure on each one.
  • Fixes it, with your approval, by opening a pull request, then checks your next bill to prove the saving was real.

Everything runs on your machine, read-only, and your billing data never leaves it.

Try it

bash
uvx nable scan
text
nable scan · profile prod
account 3521… · this account only
scanning 17 regions …
  us-east-1 ......... 3 findings
  eu-west-1 ......... 1 finding
────────────────────────────────────────────
$2,140/mo recoverable
    $1,200/mo  3 idle NAT gateways, us-east-1
      $610/mo  14 unattached EBS volumes (2.1 TB), us-east-1
      $330/mo  idle RDS instance (db.r5.xlarge, <2% CPU), eu-west-1
run `nable scan --spend` for the spend breakdown (uses Cost Explorer, ~$0.02)

Reads only free cloud APIs, so scanning never adds to your bill. uvx nable scan --demo runs on sample data with no account at all. Add --json for CI, or --spend for a deeper breakdown.

nable demo: a sample bill in seconds

Use it in your editor

uvx nable runs as a local MCP server inside Claude, Cursor, and VS Code, on your existing Claude or Cursor membership, no API key and no per-token cost. Then ask:

  • "Why did our AWS bill jump last month?"
  • "How much are we spending on OpenAI and Anthropic?"
  • "Which instances should we downsize?"
  • "Open a Jira ticket for any waste over $200/mo"

Setup

Requires Python 3.11+. Need uv? curl -LsSf https://astral.sh/uv/install.sh | sh (or brew install uv).

bash
uvx nable

The setup wizard finds AWS or GCP credentials already on your machine (an SSO login, a CLI profile, or default credentials), connects the one you pick, and configures your editor. Usually you never type a key.

Cursor one-click: Add nable to Cursor

Free forever for the local tool. A hosted version for teams (dashboards without a terminal, SSO, scheduled reports, always-on agents) is at getnable.com/pricing.

Manual editor config — only needed if setup didn't auto-configure

If finops setup doesn't auto-configure, run:

bash
finops setup claude

Or add manually to claude_desktop_config.json:

With uvx (recommended):

config.json
{
  "mcpServers": {
    "nable": { "command": "uvx", "args": ["--python", "3.12", "finops-mcp"] }
  }
}

With absolute path:

config.json
{
  "mcpServers": {
    "nable": { "command": "/usr/local/bin/finops-mcp" }
  }
}

Use the path from which finops-mcp.

Config file locations:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • Linux: ~/.config/Claude/claude_desktop_config.json

Why uvx? Claude Desktop is a GUI app and doesn't inherit your shell's PATH. uvx runs finops-mcp in its own isolated environment. It's the most reliable option on corporate machines with managed Python installs.

Give your agent cost controls — a pre-action budget gate for coding agents

nable is not just tools your agent reads from. It is a pre-action gate your agent calls before it makes a cost-affecting change: it prices the change, checks it against your budget, and offers a cheaper path. It never applies anything itself. Propose-only, your agent proposes and a human approves.

Add one line to your agent's system prompt (Claude Code, Cursor, or any MCP client):

Before you apply any infrastructure change (a terraform apply, a helm upgrade, creating or resizing a resource) or start an expensive job, first call check_action_policy with the action and the change (a terraform plan, a helm diff, or a monthly_delta_usd). Relay the verdict, the dollar impact, and the cheaper path when one is offered. Never apply a block or an escalate action; surface it to the human. nable is advisory and propose-only.

The gate returns allow / warn / block / escalate against your policy, the monthly and annual dollar impact, and a spot alternative when the change is compute. One-way doors (delete, terminate, buy a commitment) and over-budget changes always escalate to a human.

And a budget for the agent itself. Run nable ai-budget once, it asks whether you are on a flat plan or a metered API and what you pay, then remembers. On a flat plan it tracks how much subsidized compute you pull for your fixed fee and warns before you run low; on metered it gates on a dollar spend cap. check_ai_budget does the same for the agent mid-task. It reads your Claude Code usage locally, nothing uploaded. Add to your system prompt:

Before starting a large task, call check_ai_budget. If it returns warn or over, tell me where I stand before continuing.

It reports your real usage and burn rate against your budget, not a fabricated percentage of a plan's hidden rate limit.

Connectors (17) — every provider and what it pulls, plus Azure roles
ProviderWhat it pulls
AWSCost Explorer (free tier) · CUR via S3 (Pro: line-item granularity, savings plans, reservations)
AzureCost Management API · Advisor cost recs · VM rightsizing (Azure Monitor) · native budgets · forecast
GCPCloud Billing API + BigQuery export
DatadogUsage Metering API v2: real dollar amounts
SnowflakeACCOUNT_USAGE.METERING_HISTORY
LangfuseDaily metrics API: model cost, token usage, trace volume
MongoDB AtlasInvoice API
TwilioUsage Records API
CloudflareBilling API
VercelInvoice API (Enterprise)
New RelicData ingest + user counts
StripeFees and billing activity
DatabricksDBU usage and SQL warehouse spend
OpenAIAPI usage and token spend by model
AnthropicClaude API usage and token spend

Azure roles. The Azure tools span three RBAC roles, granted to the service principal on each subscription (run finops doctor to check):

bash
# repeat per subscription
az role assignment create --assignee <client-id> --role 'Cost Management Reader' --scope /subscriptions/<sub-id>
az role assignment create --assignee <client-id> --role Reader --scope /subscriptions/<sub-id>
az role assignment create --assignee <client-id> --role 'Monitoring Reader' --scope /subscriptions/<sub-id>
FAQ — free vs paid, providers, how it compares to Cost Explorer / Vantage

Is nable free? Yes. The terminal scan, every cost query, anomaly detection, all waste and rightsizing findings, and every connector are free forever. The agent team, ticket auto-creation, scheduled digests, and commitment recommendations are Pro.

Does my billing data leave my machine? No. nable is local-first and read-only by default. It reads your cost data on your machine and never uploads it, and you can confirm the no-egress behavior in the source.

What clouds and providers does it support? AWS, Azure, GCP, and Vertex; Kubernetes (Kubecost, OpenCost); AI and LLM providers (OpenAI, Anthropic, Bedrock, OpenRouter, LiteLLM, Modal, Together, Replicate, Cohere, Mistral, Langfuse); data platforms (Databricks, Snowflake, MongoDB); and SaaS (Datadog, New Relic, Cloudflare, Twilio, Vercel, Stripe).

How is it different from AWS Cost Explorer? Cost Explorer is AWS-only and console-bound. nable is cross-cloud, runs in your terminal and in Claude/Cursor, covers AI and GPU spend no cloud console shows, and proposes fixes as pull requests. nable scan also makes zero paid API calls by default.

Is there an open-source alternative to Vantage or CloudHealth? nable is an open-source (Apache-2.0), local-first alternative for cost queries, waste detection, rightsizing, and AI/GPU cost, running on your machine instead of a hosted SaaS.

Troubleshooting — install and setup fixes
bash
finops-doctor          # checks credentials, DB, network, audit log
finops setup claude    # re-run editor configuration only

Read the full README →View source on GitHub →

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars
18
Stargazers on the source repository.
Last commit
12d ago
Most recent push to the default branch.
Availability
100%
Our rolling endpoint + install checks that succeeded.
Install check
Passed
Our sandbox started it and listed its tools.
Tools exposed
10
Callable tools this server registers over MCP.
Directory activity
2 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Finopsmcp

No, all billing data is read-only and processed locally on your machine; your credentials and billing data never leave your device.

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Technical Specs & Signals

Category☁️Cloud Platforms
PricingFree
More technical detailsExpand ▾
TransportSTDIO
RuntimePython
AuthNo auth required
LicenseApache-2.0
ClientsClaude Desktop, Cursor, Windsurf
Last updatedAug 30, 2026
Views2
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars18
GitHub Star CountTotal stargazers on GitHub representing community popularity (18 stars).
Last commit12d ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Aug 30, 2026
71Quality signal: Great · 71/100How this signal is calculated ▾
Server availability25/25
Verified ownership10/20
Documentation & tools30/30
Adoption & activity6/15
Community engagement0/10

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Scanned 23d ago via OSV.dev · nable (PyPI)

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