> ## Documentation Index
> Fetch the complete documentation index at: https://runcrate.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Audit Your GPU Infrastructure with AI Agents

> Use MCP tools to list all instances, volumes, and environments, identify waste, and get a cost summary — all through conversation.

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Ask your AI agent for a full inventory of your GPU cloud. It lists every resource, calculates costs, identifies waste, and suggests optimizations.

***

## "Give me a complete audit of everything running in my workspace."

The agent inventories all resources:

1. **`list_instances`** — all GPU instances
2. **`list_volumes`** — all storage volumes
3. **`list_environments`** — all environments
4. **`billing_balance`** — current credit balance
5. **`billing_usage`** — spending over the last 30 days

> **Infrastructure Audit — May 19, 2026**
>
> **Instances (4 running):**
>
> | Instance       | Environment | GPU      | Uptime  | Cost/hr |
> | -------------- | ----------- | -------- | ------- | ------- |
> | prod-inference | production  | H100     | 12 days | \$2.50  |
> | staging-test   | staging     | A100     | 3 days  | \$1.60  |
> | dev-box        | main        | RTX 4090 | 18 hrs  | \$0.35  |
> | old-benchmark  | main        | RTX 4090 | 9 days  | \$0.35  |
>
> **Volumes (3 total):**
>
> | Volume        | Environment | Size   | Region       | Status    |
> | ------------- | ----------- | ------ | ------------ | --------- |
> | model-weights | production  | 500 GB | us-east-1    | attached  |
> | training-data | main        | 200 GB | us-east-1    | available |
> | temp-scratch  | main        | 100 GB | eu-central-1 | available |
>
> **Environments:** main, staging, production
>
> **Balance:** $1,247.80 **30-day spend:** $1,892.40
> **Current burn rate:** $4.80/hr ($115.20/day)

***

## "What's wasting money? Where can I cut costs?"

The agent analyzes utilization:

1. **`ssh_execute`** on each instance — checks GPU utilization
2. **`list_volumes`** — checks for unattached volumes

> **Waste identified:**
>
> | Resource      | Issue                               | Monthly cost | Action                     |
> | ------------- | ----------------------------------- | ------------ | -------------------------- |
> | old-benchmark | 0% GPU utilization for 9 days       | \$75.60      | Terminate                  |
> | staging-test  | 2% GPU utilization                  | \$115.20/mo  | Terminate when not testing |
> | temp-scratch  | Unattached volume, different region | \$7.50/mo    | Delete if not needed       |
> | training-data | Unattached volume                   | \$15.00/mo   | Delete or attach           |
>
> **Potential savings: \$213.30/month** (45% of current spend)
>
> Kill **old-benchmark** first (idle 9 days), then shut down **staging-test** between sessions, and delete **temp-scratch** (wrong region).

***

## "Clean up the waste. Kill idle instances and delete unused volumes."

The agent executes the cleanup:

1. **`delete_instance`** — terminates `old-benchmark`
2. **`delete_volume`** — deletes `temp-scratch`
3. **`billing_balance`** — checks updated balance after refunds

> **Cleanup complete:**
>
> * Terminated **old-benchmark** (idle 9 days) — saving \$0.35/hr
> * Deleted **temp-scratch** (100 GB, eu-central-1) — unused credits refunded
>
> **Updated burn rate:** $4.45/hr (was $4.80/hr)
> **Monthly savings:** \~\$252
>
> Remaining resources: 3 instances, 2 volumes across 3 environments.
> Next recommendation: shut down **staging-test** when you're not actively testing.

***

## Tools used in this workflow

| Tool                                                    | Purpose                            |
| ------------------------------------------------------- | ---------------------------------- |
| `list_instances` / `list_volumes` / `list_environments` | Full resource inventory            |
| `billing_balance` / `billing_usage`                     | Credit and spending data           |
| `ssh_execute`                                           | Check GPU utilization per instance |
| `delete_instance` / `delete_volume`                     | Clean up waste                     |