Connects Claude to your actual AWS, Azure, GCP, and SaaS billing data through a local-first architecture that keeps credentials and cost data on your machine. Pulls from Cost Explorer, Azure Cost Management, Cloud Billing API, and usage APIs for Datadog, Snowflake, MongoDB Atlas, Twilio, and a dozen other providers. Exposes tools for spend breakdowns, anomaly detection, rightsizing recommendations, and forecast queries. Credentials live encrypted in your OS keyring, cost data caches to local SQLite, and nothing hits a backend server. Ships with a setup wizard that auto-detects existing AWS profiles and writes your Claude config. Also includes a local web dashboard if you need to share cost visibility with non-technical stakeholders without involving the AI layer.
Open-source, local-first FinOps. Ask your whole cloud and AI bill anything, get the fix as a pull request you approve, and prove the savings on your next invoice.
nable is an MCP server that runs on your machine and connects to your real AWS, Azure, GCP, Kubernetes, and SaaS billing. It answers cost questions in your editor, finds waste, drafts the fix for your approval, and verifies the savings landed. Your credentials stay in your OS keychain and your bill never leaves your control, so the no-egress claim is something you can read in the code, not just take on faith. The local agent is open and auditable; a hosted platform is available for teams.
getnable.com · docs, quickstart, and the hosted platform

User: Just downloaded nable: What's our cloud spend this month?
Claude: Here's your spend breakdown:
Total: $8,421.63 / month
Provider | Spend
------------|----------
AWS | $7,284.17
Datadog | $847.20
Snowflake | $290.26
Top AWS services:
- EC2: $3,184.52
- EKS: $1,821.34
- RDS: $1,243.80
- ElastiCache: $612.40
- S3: $184.22
Most spend is concentrated in us-east-1 ($5,841 of the $7,284 AWS total).
Requires Python 3.10 or newer. The uvx command below fetches a matching Python for you. If you take the pip path instead, check yours first with python --version (or python3 --version). On older Python, pip reports No matching distribution found for finops-mcp.
Step 1: Install and run the setup wizard
Need uv? It is not preinstalled on macOS or most Linux:
curl -LsSf https://astral.sh/uv/install.sh | sh # macOS / Linux
# or: brew install uv
Then:
uvx nable
No uv and don't want it? On Python 3.10+, pip install -U finops-mcp && finops welcome works too.
First run downloads dependencies, so give it a moment before the welcome screen appears.
The wizard walks through connecting your providers and auto-configures Claude Desktop at the end. No config file editing, no manual env vars.
Using Cursor? One-click install (opens Cursor and adds nable):
Then run finops setup once to connect a cloud account.
On Anaconda? Use uvx (isolated, won't touch your Anaconda environment):
brew install uv && uvx nable setup
Step 2: Connect AWS (usually one keystroke)
finops setup aws
The wizard checks for AWS credentials you already have (an SSO login, an AWS CLI profile, or default credentials), shows you the account it found, and connects it when you confirm. If you use aws on this machine already, you will not type a single key.
Checking for AWS credentials on this machine...
✓ Found working credentials: profile 'default' -> account 1234
Connect this account? [Y/n]
Only if no working credentials are found does it walk you through creating a read-only access key. Want the IAM policy to hand your platform team first? Run finops setup aws --iam-template.
Step 3: Restart Claude Desktop and ask
What are my AWS costs this month?
Once you see a real cost breakdown, you're live. Also works with Cursor, Windsurf, and VS Code.
Step 4 (optional): Open the visual dashboard
finops serve
Serves a password-protected web dashboard at http://localhost:8080, local to your machine by default. To let your team or manager view it in a browser (no Claude required), add --host 0.0.0.0 so it binds your network. It stays password-protected; share the URL and password with them.
7-day free trial, all features unlocked. No credit card required.
To add more providers later:
finops setup aws # add another AWS account
finops setup azure # add Azure
finops setup slack # configure alerts
finops setup license # activate a Team plan key
finops serve # open the visual dashboard
finops serve
Starts a local web dashboard your whole team can open in a browser, no Claude Desktop required. Share it with an exec, a FinOps analyst, or anyone who needs to see costs without using an AI interface.
What it shows:
The dashboard reads from your local provider connections. Your data stays on your machine.
# Secure with a password (recommended when sharing on a network)
FINOPS_DASHBOARD_PASSWORD=yourpassword finops serve
# Default: auto-generates a random password and prints it at startup
finops serve
Light mode, dark mode, and 30/60/90-day lookback are built in.
Your credentials are encrypted with Fernet and stored in your OS keyring (macOS Keychain, Windows Credential Manager, or libsecret on Linux). They never leave your machine. Cost data is cached in a local SQLite database, and nable has no backend, so we never see your cost data or credentials. One honest caveat: when you ask a question in your AI editor, the figures nable returns go to your editor's own AI to answer it, the same as any prompt, never to a nable server. If you need zero AI exposure, use the local dashboard (finops serve) or CLI, which never touch a model. Teams share findings via Slack alerts, Notion publishing, and CSV exports. No shared database required.
nable is read-only by default. It never writes to your AWS account unless you explicitly enable cleanup mode. Run finops setup aws --iam-template to generate a least-privilege IAM policy with exactly the permissions nable needs.
None of this is take-our-word-for-it. Read the source, check the OpenSSF Scorecard, run finops-doctor to see exactly what nable touches, and set NABLE_NO_TELEMETRY=1 (or FINOPS_AIRGAP=1 to forbid every non-provider request) if you want it locked down.
If finops setup doesn't auto-configure, run:
finops setup claude
Or add manually to claude_desktop_config.json:
With uvx (recommended):
{
"mcpServers": {
"nable": { "command": "uvx", "args": ["--python", "3.12", "finops-mcp"] }
}
}
With absolute path:
{
"mcpServers": {
"nable": { "command": "/usr/local/bin/finops-mcp" }
}
}
Use the path from which finops-mcp.
Config file locations:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json~/.config/Claude/claude_desktop_config.jsonWhy uvx? Claude Desktop is a GUI app and doesn't inherit your shell's PATH. uvx sidesteps this by running finops-mcp in its own isolated environment. It's the most reliable option on corporate machines with managed Python installs.
| Provider | What it pulls |
|---|---|
| AWS | Cost Explorer (free tier) · CUR via S3 (Pro: line-item granularity, savings plans, reservations) |
| Azure | Cost Management API · Advisor cost recs · VM rightsizing (Azure Monitor) · native budgets · forecast |
| GCP | Cloud Billing API + BigQuery export |
| Datadog | Usage Metering API v2: real dollar amounts |
| Snowflake | ACCOUNT_USAGE.METERING_HISTORY |
| Langfuse | Daily metrics API: model cost, token usage, trace volume |
| MongoDB Atlas | Invoice API |
| Twilio | Usage Records API |
| Cloudflare | Billing API |
| GitHub | Actions minutes + Copilot seats |
| Vercel | Invoice API (Enterprise) |
| PagerDuty | Seat count |
| New Relic | Data ingest + user counts |
| Stripe | Fees and billing activity |
| Databricks | DBU usage and SQL warehouse spend |
| OpenAI | API usage and token spend by model |
| Anthropic | Claude API usage and token spend |
Azure roles. The Azure tools span three RBAC roles, granted to the service
principal on each subscription. Without them, the affected tools return empty
results (run finops doctor to check):
| Role | Unlocks |
|---|---|
| Cost Management Reader | cost queries, budgets, forecast, cost-by-dimension |
| Reader | Azure Advisor recommendations + VM list (rightsizing) |
| Monitoring Reader | VM CPU metrics (rightsizing) |
# 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>
nable is not just a connector that pipes billing data into Claude. It runs active analysis on your infrastructure and surfaces findings as tools Claude can reason about and act on.
Every finding is classified by how sure we are. A recommendation is something nable measured: a precise dollar figure, a safe fix, and a check that the savings actually landed on your next bill. An investigation is a signal worth confirming: an honest order-of-magnitude, never a fake-precise number, with the steps to confirm it. nable proposes, you approve, and it verifies. It never changes your infrastructure on its own.
AWS deep audit goes well beyond Cost Explorer. It pulls CloudWatch metrics for every running resource and flags waste that never shows up on your bill: gp2 volumes that should be gp3 (20% cheaper, same performance), unattached EBS volumes, idle NAT Gateways costing $32/mo in base charges, RDS backup retention set way too high, CloudWatch Log Groups with no retention policy growing forever, and Lambda functions allocated 2x the memory they actually use. Think of it as Compute Optimizer plus the layer underneath it.
Anomaly detection uses z-score, CUSUM drift, and day-of-week seasonal normalization. When something spikes, it drills into Cost Explorer by tag and tells you which team, environment, or service drove it. Anomaly findings and Slack/Teams alerts are free; auto-ticketing is a paid feature.
Rightsizing combines AWS Compute Optimizer with nable's own CloudWatch analysis. It gives you specific recommended instance types with estimated savings, not just a list of underutilized resources. Recommendations are free; ticket auto-creation is a paid feature.
Commitment analysis (a paid feature) models Savings Plans and Reserved Instance coverage against your actual usage. It shows your current effective discount rate, coverage gaps, and what you would save by purchasing additional commitments.
The local agent is open-source and free: the MCP server, every connector, cost queries, anomaly detection, rightsizing, AI and LLM spend tracking, the local dashboard, and remediation drafts (the PRs and tickets you approve). Run it on your machine, audit it, fork the connectors.
A hosted platform is available for teams who would rather have it run for them: a managed, single-tenant workspace with dashboards anyone can use without a terminal, SSO and roles, scheduled reports, and a managed AI agent. Single-tenant by design, your bill is never pooled with anyone else's.
See getnable.com for the current plans and a free trial.
finops-doctor # checks credentials, DB, network, audit log
finops setup claude # re-run Claude Desktop configuration only
| Symptom | Fix |
|---|---|
| Tools don't appear in Claude | Switch to uvx config or use absolute path |
command not found: finops-mcp | Re-install with pip install finops-mcp or use uvx |
| AWS returns no data | Run finops setup aws. The wizard writes credentials to your editor config automatically. |
No matching distribution found for finops-mcp | Your Python is older than 3.10. Check with python --version, then install on 3.10+ (uvx nable, or python3.10 -m pip install finops-mcp). |
| Python 3.8/3.9 errors | nable requires Python 3.10+: python3.10 -m pip install finops-mcp |
| Corporate SSL errors | pip install --trusted-host pypi.org --trusted-host files.pythonhosted.org finops-mcp |
| Permission denied | Install to user: pip install --user finops-mcp or use uvx |
| Works at home, not at work | Use uvx (corporate IT often strips custom PATH entries) |
Full setup guide: getnable.com/docs
mcp-name: io.github.chaandannn/finops-mcp
io.github.ericm1018/skillfm-llm-cost-optimizer-openai-anthropic-usage
io.github.mikerawsonnz/llm-orchestration-agent
io.github.mikerawsonnz/authenticated-llm-agent
labforgedev/copilot-memory-mcp
csoai-org/agent-prompt-injection-firewall-mcp
io.github.mikerawsonnz/authenticated-multi-llm-agent