VMware AIops

https://github.com/zw008/vmware-aiops
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VMware AIops is an AI-powered VMware vCenter/ESXi VM lifecycle and deployment tool with 31 tools...
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### VM lifecycle management example

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/goose.md

Example interaction for cloning VMs.

```text
You: Clone vm-template to create 3 new web servers, name them web04/web05/web06

Goose: [calls vm_create_plan, then vm_apply_plan]
Plan created: clone vm-template × 3
Step 1/3: Deploying web04... ✓
Step 2/3: Deploying web05... ✓
Step 3/3: Deploying web06... ✓
```

--------------------------------

### Example: Get VM Details

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/continue.md

Shows how to use vmware-aiops through Continue to retrieve detailed information about a specific virtual machine. This example utilizes the `vm_info` tool to fetch VM status, resources, OS, IP, snapshots, and datastore details.

```markdown
You: @vmware-aiops Get details for vm-app01

Continue: [calls vm_info]
vm-app01:
  Power: ON | vCPU: 8 | RAM: 32GB (28GB used)
  Guest OS: Ubuntu 22.04 | IP: 10.0.1.45
  Snapshots: 2 (oldest: 14 days ago)
  Datastore: ssd-ds01 (free: 450GB)
```

--------------------------------

### Install via PyPI

Source: https://github.com/zw008/vmware-aiops/blob/main/README-CN.md

Standard installation methods using Python package managers.

```bash
uv tool install vmware-aiops
```

```bash
pip install vmware-aiops
```

```bash
pip install vmware-aiops -i https://pypi.tuna.tsinghua.edu.cn/simple
```

--------------------------------

### Guest operations example

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/goose.md

Example interaction for executing commands on a guest VM.

```text
You: Run "df -h" on vm-linux01 and show disk usage

Goose: [calls vm_guest_exec_output]
Filesystem      Size  Used Avail Use%
/dev/sda1        50G   32G   18G  64%
/dev/sdb1       200G  180G   20G  90% ← nearing capacity
```

--------------------------------

### Deploy VM from template example

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/cursor.md

Example of cloning a template to create a new VM via Cursor.

```text
You: Clone dev-template to create a new VM named test-env-01

Cursor: [calls vm_create_plan, then vm_apply_plan]
Plan: clone dev-template → test-env-01
Executing... ✓ VM deployed successfully.
```

--------------------------------

### Install Aider Chat and Serve Ollama

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Install the Aider Chat Python package and start the Ollama service. This is a prerequisite for running Aider with local models.

```bash
pip install aider-chat
ollama serve
```

--------------------------------

### Local Installation for Claude Code

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Manual setup steps to clone, register, and enable the plugin locally.

```bash
# Clone and symlink
git clone https://github.com/zw008/VMware-AIops.git
ln -sf $(pwd)/VMware-AIops ~/.claude/plugins/marketplaces/vmware-aiops

# Register marketplace
python3 -c "
import json, pathlib
f = pathlib.Path.home() / '.claude/plugins/known_marketplaces.json'
d = json.loads(f.read_text()) if f.exists() else {}
d['vmware-aiops'] = {
    'source': {'source': 'github', 'repo': 'zw008/VMware-AIops'},
    'installLocation': str(pathlib.Path.home() / '.claude/plugins/marketplaces/vmware-aiops')
}
f.write_text(json.dumps(d, indent=2))
"

# Enable plugin
python3 -c "
import json, pathlib
f = pathlib.Path.home() / '.claude/settings.json'
d = json.loads(f.read_text()) if f.exists() else {}
d.setdefault('enabledPlugins', {})['vmware-ops@vmware-aiops'] = True
f.write_text(json.dumps(d, indent=2))
"
```

```bash
/vmware-ops:vmware-aiops
```

--------------------------------

### Query infrastructure example

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/cursor.md

Example of querying powered-on VMs via Cursor chat.

```text
You: How many VMs are powered on in my vCenter?

Cursor: [calls list_virtual_machines with power_state=poweredOn]
Found 42 powered-on VMs across 3 clusters.
```

--------------------------------

### Install Companion Skills

Source: https://github.com/zw008/vmware-aiops/blob/main/README-CN.md

Commands to install related monitoring, storage, and Kubernetes management skills.

```bash
uv tool install vmware-monitor
```

```bash
uv tool install vmware-storage
```

```bash
uv tool install vmware-vks
```

--------------------------------

### Install and Use OpenAI Codex CLI

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Setup steps for integrating VMware-AIops skills into the Codex CLI.

```bash
# Install Codex CLI
npm i -g @openai/codex
# Or on macOS:
# brew install --cask codex

# Copy skill to Codex skills directory
mkdir -p ~/.codex/skills/vmware-aiops
cp codex-skill/SKILL.md ~/.codex/skills/vmware-aiops/SKILL.md

# Copy AGENTS.md to project root
cp codex-skill/AGENTS.md ./AGENTS.md
```

```bash
codex --enable skills
> List all VMs on my ESXi
```

--------------------------------

### Install and Use Gemini CLI

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Installation commands for the Gemini CLI extension.

```bash
# Install Gemini CLI
npm install -g @google/gemini-cli

# Install the extension from the cloned repo
gemini extensions install ./gemini-extension

# Or install directly from GitHub
# gemini extensions install https://github.com/zw008/VMware-AIops
```

```bash
gemini
> Show me all VMs on my ESXi host
```

--------------------------------

### Install vmware-monitor

Source: https://github.com/zw008/vmware-aiops/blob/main/examples/ollama-local-setup.md

Install vmware-monitor for read-only operations in production environments.

```bash
uv tool install vmware-monitor
```

--------------------------------

### Install and Configure vmware-aiops

Source: https://github.com/zw008/vmware-aiops/blob/main/examples/mcp-configs/README.md

Initial setup for the CLI tool and credential file structure. Requires manual editing of the generated config and environment files.

```bash
# Install vmware-aiops
uv tool install vmware-aiops
# or: pip install vmware-aiops

# Configure credentials
mkdir -p ~/.vmware-aiops
cp config.example.yaml ~/.vmware-aiops/config.yaml
cp .env.example ~/.vmware-aiops/.env
chmod 600 ~/.vmware-aiops/.env
# Edit config.yaml and .env with your vCenter/ESXi details
```

--------------------------------

### Development Environment Setup

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/setup-guide.md

Commands to clone the repository and set up a local development environment using uv.

```bash
git clone https://github.com/zw008/VMware-AIops.git
cd VMware-AIops
uv venv && source .venv/bin/activate
uv pip install -e .
```

--------------------------------

### Configure Continue CLI

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Setup instructions for Continue CLI and local model configuration.

```bash
# Install Continue CLI
npm i -g @continuedev/cli

# Copy rules file
mkdir -p .continue/rules
cp codex-skill/AGENTS.md .continue/rules/vmware-aiops.md
```

```yaml
models:
  - name: local-coder
    provider: ollama
    model: qwen2.5-coder:32b
```

```bash
cn
> Check ESXi health and alarms
```

--------------------------------

### Run command inside VM example

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/cursor.md

Example of executing a command within a guest VM via Cursor.

```text
You: Check disk usage on vm-linux01

Cursor: [calls vm_guest_exec_output]
Filesystem      Size  Used Avail Use%
/dev/sda1        50G   32G   18G  64%
/dev/sdb1       200G  180G   20G  90% ← nearing capacity
```

--------------------------------

### Natural language query example

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/goose.md

Example interaction for querying VM status.

```text
You: Which VMs have been powered off for more than 7 days?

Goose: [calls list_virtual_machines, get_events]
Found 4 powered-off VMs idle > 7 days:
- vm-test-old (14 days), vm-dev-unused (21 days) ...
```

--------------------------------

### Install and Initialize VMware AIops

Source: https://context7.com/zw008/vmware-aiops/llms.txt

Commands to install the tool, set up the configuration directory, and verify connectivity.

```bash
# Install via uv (recommended)
uv tool install vmware-aiops

# Or via pip
pip install vmware-aiops

# Create configuration directory
mkdir -p ~/.vmware-aiops

# Generate config templates
vmware-aiops init

# Set permissions on credentials file
chmod 600 ~/.vmware-aiops/.env

# Verify installation and connectivity
vmware-aiops doctor
```

--------------------------------

### Set Up VMware AI Ops Environment Variables

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Steps to copy the example .env file for storing passwords, edit it with credentials, and set secure file permissions.

```bash
# Use the template
cp .env.example ~/.vmware-aiops/.env

# Edit and fill in your passwords, then lock permissions
chmod 600 ~/.vmware-aiops/.env
```

--------------------------------

### Install vmware-aiops

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/localcowork.md

Installs the vmware-aiops tool using the uv package manager. Ensure uv is installed and configured.

```bash
uv tool install vmware-aiops
```

--------------------------------

### Create and Configure VMware AI Ops Configuration File

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Instructions to create the configuration directory, copy the example configuration file, and edit it with vCenter/ESXi targets.

```bash
mkdir -p ~/.vmware-aiops
cp config.example.yaml ~/.vmware-aiops/config.yaml
# Edit config.yaml with your vCenter/ESXi targets
```

--------------------------------

### Install vmware-aiops via PyPI

Source: https://github.com/zw008/vmware-aiops/blob/main/RELEASE_NOTES.md

Use this command to install the package using the uv tool.

```bash
uv tool install vmware-aiops==1.1.0
```

--------------------------------

### Install Software Inside VM via Guest Exec

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Installs software within a running VM using guest execution. Requires specifying the VM name, command, arguments, and user.

```bash
vmware-aiops vm guest-exec lab-vm --cmd /bin/bash --args "-c 'apt-get install -y nginx'" --user root
```

--------------------------------

### Install and Run Aider

Source: https://github.com/zw008/vmware-aiops/blob/main/examples/ollama-local-setup.md

Install the Aider chat client and run it with Ollama and vmware-aiops conventions for interactive command execution.

```bash
pip install aider-chat
```

```bash
aider --conventions codex-skill/AGENTS.md --model ollama/qwen2.5-coder:32b
```

--------------------------------

### Guest Provisioning with Python

Source: https://context7.com/zw008/vmware-aiops/llms.txt

Automates VM setup by running a sequence of guest operations (upload, exec, service) using a Python script. Requires VMware Tools.

```python
# MCP Tool: vm_guest_provision
# Provision a VM with SSH key, software install, and service start

steps = [
    {"type": "upload", "local_path": "~/.ssh/id_rsa.pub", "guest_path": "/root/.ssh/authorized_keys"},
    {"type": "exec", "command": "chmod 600 /root/.ssh/authorized_keys"},
    {"type": "exec", "command": "apt-get update && apt-get install -y nginx"},
    {"type": "service", "name": "nginx", "action": "enable"},
    {"type": "service", "name": "nginx", "action": "start"},
]

result = vm_guest_provision(
    vm_name="web-server",
    username="root",
    password="guest-password",
    steps=steps,
    timeout=300
)
```

--------------------------------

### Define Operation List for vm_create_plan

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/plans/2026-03-09-plan-apply-design.md

Example input structure for the vm_create_plan tool, containing a list of actions to be performed on a VM.

```json
{
  "operations": [
    {"action": "power_off", "vm_name": "test-1"},
    {"action": "revert_snapshot", "vm_name": "test-1", "snapshot": "baseline"},
    {"action": "power_on", "vm_name": "test-1"}
  ]
}
```

--------------------------------

### Initialize VMware-AIops Environment

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Standard installation and initialization sequence for the CLI tool.

```bash
uv tool install vmware-aiops
mkdir -p ~/.vmware-aiops
vmware-aiops init  # generates config.yaml and .env templates
chmod 600 ~/.vmware-aiops/.env
```

--------------------------------

### Deploy Lab Environment Workflow

Source: https://context7.com/zw008/vmware-aiops/llms.txt

Command-line steps to deploy a lab environment, starting from browsing datastore for OVA images to setting a time-to-live for auto-cleanup.

```bash
# 1. Browse datastore for OVA images
vmware-aiops datastore browse datastore1 --pattern "*.ova"
```

```bash
# 2. Deploy VM from OVA
vmware-aiops deploy ova ./ubuntu-24.04.ova --name lab-vm --datastore datastore1
```

```bash
# 3. Power on the VM
vmware-aiops vm power-on lab-vm
```

```bash
# 4. Install software inside VM
vmware-aiops vm guest-exec-output lab-vm \
  --cmd "apt-get update && apt-get install -y nginx docker.io" \
  --user root
```

```bash
# 5. Create baseline snapshot
vmware-aiops vm snapshot-create lab-vm --name baseline
```

```bash
# 6. Set TTL for auto-cleanup (8 hours)
vmware-aiops vm set-ttl lab-vm --minutes 480
```

--------------------------------

### Common Workflow: Deploy Lab Environment

Source: https://context7.com/zw008/vmware-aiops/llms.txt

A step-by-step bash script demonstrating the deployment of a lab environment using an OVA image, software installation, and setting up a cleanup timer.

```APIDOC
## Common Workflow: Deploy Lab Environment

### Description
Complete workflow for deploying a lab environment with OVA image, software installation, and baseline snapshot.

### Steps
1. **Browse datastore for OVA images**
   ```bash
   vmware-aiops datastore browse datastore1 --pattern "*.ova"
   ```
2. **Deploy VM from OVA**
   ```bash
   vmware-aiops deploy ova ./ubuntu-24.04.ova --name lab-vm --datastore datastore1
   ```
3. **Power on the VM**
   ```bash
   vmware-aiops vm power-on lab-vm
   ```
4. **Install software inside VM**
   ```bash
   vmware-aiops vm guest-exec-output lab-vm \
     --cmd "apt-get update && apt-get install -y nginx docker.io" \
     --user root
   ```
5. **Create baseline snapshot**
   ```bash
   vmware-aiops vm snapshot-create lab-vm --name baseline
   ```
6. **Set TTL for auto-cleanup (8 hours)**
   ```bash
   vmware-aiops vm set-ttl lab-vm --minutes 480
   ```
```

--------------------------------

### Batch deployment pipeline

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/mcp-agent.md

Example of using an agent to perform batch VM deployment with TTL settings.

```python
# Deploy 5 VMs from spec and set 24h TTL for auto-cleanup
result = await agent.send(
    "Deploy 5 VMs from template ubuntu-22-base, "
    "name them test-01 through test-05, "
    "set TTL of 24 hours on each"
)
```

--------------------------------

### Install vmware-avi Tool

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Installs the vmware-avi tool for load balancer management (AVI, ALB, AKO, Ingress).

```bash
uv tool install vmware-avi
```

--------------------------------

### Install VMware-AIops via Package Managers

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/setup-guide.md

Use these commands to install the package using different registry sources.

```bash
# Via PyPI (recommended for version pinning)
uv tool install vmware-aiops==1.2.3

# Via Skills.sh (fetches from GitHub)
npx skills add zw008/VMware-AIops

# Via ClawHub (fetches from ClawHub registry snapshot of GitHub)
clawhub install vmware-aiops
```

--------------------------------

### Install VMware AIops via ClawHub

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Install the tool using the ClawHub command-line interface.

```bash
clawhub install vmware-aiops
```

--------------------------------

### Install Kimi Code Skill

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Command to register the skill file in the Kimi skills directory.

```bash
# Copy skill file to Kimi skills directory
mkdir -p ~/.kimi/skills/vmware-aiops
cp kimi-skill/SKILL.md ~/.kimi/skills/vmware-aiops/SKILL.md
```

--------------------------------

### Example: Deploy VM with Auto-Cleanup TTL

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/continue.md

Illustrates deploying a test virtual machine from a template and setting a Time-To-Live (TTL) for automatic deletion using vmware-aiops and Continue. This involves a sequence of calls to `vm_create_plan`, `vm_apply_plan`, and `vm_set_ttl`.

```markdown
You: @vmware-aiops Deploy a test VM from ubuntu-22-base with 4h TTL

Continue: [calls vm_create_plan → vm_apply_plan → vm_set_ttl]
✓ vm-test-1741694400 deployed
✓ TTL set: auto-delete at 2026-03-12 08:00 UTC
```

--------------------------------

### Install vmware-storage Tool

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Installs the vmware-storage tool for managing storage like iSCSI, vSAN, and datastores.

```bash
uv tool install vmware-storage
```

--------------------------------

### Configure VMware-AIops Environment

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/setup-guide.md

Steps to install, verify, and initialize the configuration directory and environment variables.

```bash
# 1. Install from PyPI (source: github.com/zw008/VMware-AIops)
uv tool install vmware-aiops

# 2. Verify installation source
vmware-aiops --version  # confirms installed version

# 3. Configure
mkdir -p ~/.vmware-aiops
vmware-aiops init  # generates config.yaml and .env templates
chmod 600 ~/.vmware-aiops/.env
# Edit ~/.vmware-aiops/config.yaml and .env with your target details
```

--------------------------------

### Install vmware-nsx-mgmt Tool

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Installs the vmware-nsx-mgmt tool for NSX networking tasks such as segments and gateways.

```bash
uv tool install vmware-nsx-mgmt
```

--------------------------------

### Configure MCP Server

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Installation and configuration for MCP-compatible clients like Claude Desktop.

```bash
# Run via uvx (recommended — works with uv tool install)
uvx --from vmware-aiops vmware-aiops-mcp

# With a custom config path
VMWARE_AIOPS_CONFIG=/path/to/config.yaml uvx --from vmware-aiops vmware-aiops-mcp
```

```json
{
  "mcpServers": {
    "vmware-aiops": {
      "command": "uvx",
      "args": ["--from", "vmware-aiops", "vmware-aiops-mcp"],
      "env": {
        "VMWARE_AIOPS_CONFIG": "/path/to/config.yaml"
      }
    }
  }
}
```

```bash
npx -y @smithery/cli install @zw008/VMware-AIops --client claude
```

--------------------------------

### Install vmware-nsx-security Tool

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Installs the vmware-nsx-security tool for NSX security features like DFW rules.

```bash
uv tool install vmware-nsx-security
```

--------------------------------

### Install VMware AIops via Skills.sh

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Use this command to install the tool via the Skills.sh platform, compatible with various AI agents.

```bash
npx skills add zw008/VMware-AIops
```

--------------------------------

### Install via AI Tools

Source: https://github.com/zw008/vmware-aiops/blob/main/README-CN.md

Commands to add the toolset using AI-integrated package managers.

```bash
npx skills add zw008/VMware-AIops
```

```bash
clawhub install vmware-aiops
```

--------------------------------

### Run Aider with Ollama

Source: https://github.com/zw008/vmware-aiops/blob/main/examples/mcp-configs/README.md

Example command for running Aider with a local Ollama model.

```bash
# Example: Aider + Ollama + vmware-aiops CLI
aider --conventions codex-skill/AGENTS.md --model ollama/qwen2.5-coder:32b

# Example: Continue + Ollama + MCP Server
# Configure Continue with Ollama model + vmware-aiops MCP server
```

--------------------------------

### Install VMware AIops via pip

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Standard installation using pip. A China mainland mirror is provided for faster downloads.

```bash
pip install vmware-aiops
```

```bash
pip install vmware-aiops -i https://pypi.tuna.tsinghua.edu.cn/simple
```

--------------------------------

### Install and Use Claude Code Plugin

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Commands to install the plugin via marketplace and execute VMware operations within Claude Code.

```bash
/plugin marketplace add zw008/VMware-AIops
/plugin install vmware-ops
```

```bash
/vmware-ops:vmware-aiops
> Show me all VMs on esxi-lab.example.com
```

--------------------------------

### Run Aider with Ollama

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/setup-guide.md

Example command for running Aider with local conventions and a specific Ollama model.

```bash
# Example: Aider + Ollama (fully local, no cloud API)
aider --conventions codex-skill/AGENTS.md --model ollama/qwen2.5-coder:32b
```

--------------------------------

### Configure VS Code Copilot MCP server

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/vscode-copilot.md

Provides configuration examples for both workspace-specific and user-level MCP server settings.

```json
{
  "servers": {
    "vmware-aiops": {
      "type": "stdio",
      "command": "python",
      "args": ["-m", "mcp_server"],
      "cwd": "/path/to/VMware-AIops",
      "env": {
        "VMWARE_AIOPS_CONFIG": "${env:HOME}/.vmware-aiops/config.yaml"
      }
    }
  }
}
```

```json
{
  "github.copilot.chat.mcp.enabled": true,
  "mcp": {
    "servers": {
      "vmware-aiops": {
        "type": "stdio",
        "command": "python",
        "args": ["-m", "mcp_server"],
        "cwd": "/path/to/VMware-AIops",
        "env": {
          "VMWARE_AIOPS_CONFIG": "/Users/your-name/.vmware-aiops/config.yaml"
        }
      }
    }
  }
}
```

--------------------------------

### Run Aider with Ollama and VMware AI Ops

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Example command to run Aider with Ollama and the VMware AI Ops integration, using a specific model and convention file.

```bash
aider --conventions codex-skill/AGENTS.md --model ollama/qwen2.5-coder:32b
```

--------------------------------

### Run Goose Session

Source: https://github.com/zw008/vmware-aiops/blob/main/examples/ollama-local-setup.md

Start a Goose session and interact with VMware using natural language commands.

```bash
goose session
> Check health status of all my VMware hosts
```

--------------------------------

### Run Aider with Local Qwen Model

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Configure Aider to use the local Qwen 2.5 Coder 32B model served by Ollama. This setup is recommended for local coding assistance.

```bash
# Aider + local Qwen (recommended)

  --model ollama/qwen2.5-coder:32b
```

--------------------------------

### Copilot usage examples

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/vscode-copilot.md

Demonstrates natural language interaction with the vmware-aiops MCP server for common infrastructure tasks.

```text
You: @vmware-aiops Show active alarms in prod-vcenter

Copilot: [calls get_alarms with target=prod-vcenter]
3 active alarms:
- CRITICAL: vm-api-gateway — disk I/O latency > 50ms
- WARNING: esxi-03 — CPU utilization 88%
- WARNING: datastore-nvme — 78% capacity used
```

```text
You: @vmware-aiops Deploy vm-test from template ubuntu-22-base,
     4 vCPU, 8GB RAM, set 8h TTL

Copilot: [calls vm_create_plan → vm_apply_plan → vm_set_ttl]
✓ vm-test deployed to esxi-02 / ssd-ds01
✓ TTL: auto-delete at 20:00 UTC today
IP: 10.0.2.87 (available in ~30s after tools install)
```

```text
You: @vmware-aiops Run "systemctl status my-service" on vm-backend01

Copilot: [calls vm_guest_exec]
● my-service.service
   Active: failed (Result: exit-code) since ...
   → Service crashed. Check /var/log/my-service/error.log
```

--------------------------------

### Clone VMware AI Ops Repository and Set Up Virtual Environment

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Steps to clone the VMware AI Ops repository, create a Python virtual environment, activate it, and install the backend package.

```bash
git clone https://github.com/zw008/VMware-AIops.git
cd VMware-AIops
python3 -m venv .venv
source .venv/bin/activate
pip install -e .
```

--------------------------------

### Aider Natural Language Commands

Source: https://github.com/zw008/vmware-aiops/blob/main/examples/ollama-local-setup.md

Examples of natural language prompts to execute VMware operations using Aider.

```text
> List all VMs on my lab ESXi
> Show active alarms on vcenter-prod
> What's the datastore usage?
```

--------------------------------

### Install and Verify VMware AIops

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Use these commands to install the core vmware-aiops tool and verify the installation status of the VMware family modules.

```bash
uv tool install vmware-aiops
vmware-aiops doctor
vmware-aiops hub status   # see which family members are installed
```

--------------------------------

### List powered-off VMs

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/localcowork.md

Example of querying LocalCowork to list all virtual machines that are currently powered off. This demonstrates the inventory capabilities.

```text
You: List all VMs that are powered off

LocalCowork: [calls list_virtual_machines with power_state=off]
Found 4 powered-off VMs:
- vm-backup01 (4 vCPU, 8GB RAM)
- vm-test02 (2 vCPU, 4GB RAM)
- vm-old-db (8 vCPU, 32GB RAM)
- vm-staging (4 vCPU, 16GB RAM)
```

--------------------------------

### Deploy VM from template with plan

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/localcowork.md

Demonstrates a safe, multi-step VM deployment process using LocalCowork. It first creates a deployment plan and then applies it after confirmation. This ensures resources are allocated and the deployment is validated.

```text
You: Deploy a new VM from template "ubuntu-22.04-base" with 4 vCPU and 8GB RAM

LocalCowork: [calls vm_create_plan]
Plan ready:
  - Source: ubuntu-22.04-base
  - Resources: 4 vCPU / 8GB RAM
  - Target datastore: datastore01 (free: 1.2TB)

Confirm to apply? (yes/no)
You: yes
[calls vm_apply_plan] ✓ VM deployed in 45s
```

--------------------------------

### Example: Check Critical Alarms

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/continue.md

Demonstrates how to query vmware-aiops via Continue for critical alarms in your VMware environment. This uses the `get_alarms` tool to retrieve and display alarm information.

```markdown
You: @vmware-aiops Are there any critical alarms right now?

Continue: [calls get_alarms]
2 critical alarms on prod-vcenter:
- vm-db01: Memory usage at 98% (threshold: 90%)
- esxi-host02: CPU ready time high (12ms avg)
```

--------------------------------

### Infrastructure health check example

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/goose.md

Example interaction for checking active alarms.

```text
You: Show me all active alarms in my vCenter

Goose: [calls get_alarms]
Found 3 active alarms on prod-vcenter:
- vm-web01: CPU usage critical (92%)
- datastore01: Low disk space (85% used)
- host02: Memory balloon active
```

--------------------------------

### Execute command in VM guest

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/localcowork.md

Example of using LocalCowork to execute a command within a virtual machine's guest operating system. This is useful for checking service status or running scripts remotely.

```text
You: Check nginx status on vm-web01

LocalCowork: [calls vm_guest_exec]
● nginx.service - A high performance web server
   Loaded: loaded (/lib/systemd/system/nginx.service)
   Active: active (running) since Mon 2026-03-10 08:12:33 UTC; 23h ago
```

--------------------------------

### Create a New VM

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/cli-reference.md

Create a new virtual machine with specified CPU, memory, and disk size.

```bash
vmware-aiops vm create <name> [--cpu <n>] [--memory <mb>] [--disk <gb>]
```

--------------------------------

### Check Hub Status

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Displays the status of installed family members and provides installation commands.

```bash
vmware-aiops hub status
```

--------------------------------

### Create VM

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Creates a new virtual machine with specified CPU, memory, and disk size.

```bash
vmware-aiops vm create <name> --cpu 4 --memory 8192 --disk 100
```

--------------------------------

### Install vmware-vks Tool

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Installs the vmware-vks tool for managing Tanzu Kubernetes on vSphere 8.x+.

```bash
uv tool install vmware-vks
```

--------------------------------

### Deploy Experimental Environment

Source: https://github.com/zw008/vmware-aiops/blob/main/README-CN.md

Common workflow commands for browsing datastores, deploying VMs from OVA, and configuring lifecycle settings.

```bash
vmware-aiops datastore browse <ds> --pattern "*.ova"
vmware-aiops deploy ova ./image.ova --name lab-vm --datastore ds1
vmware-aiops vm guest-exec lab-vm --cmd /bin/bash --args "-c 'apt-get install -y nginx'" --user root
vmware-aiops vm snapshot-create lab-vm --name baseline
vmware-aiops vm set-ttl lab-vm --minutes 480
```

--------------------------------

### Apply VM Creation Plan

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Executes a previously created VM plan sequentially. The process stops if any step fails.

```bash
vm_apply_plan
```

--------------------------------

### Install vmware-aria Tool

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Installs the vmware-aria tool for Aria Ops metrics, alerts, and capacity management.

```bash
uv tool install vmware-aria
```

--------------------------------

### Install VMware Family Modules

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Individual installation commands for extending the core vmware-aiops functionality with specialized modules.

```bash
uv tool install vmware-monitor
```

```bash
uv tool install vmware-storage
```

```bash
uv tool install vmware-vks
```

```bash
uv tool install vmware-nsx-mgmt
```

```bash
uv tool install vmware-nsx-security
```

```bash
uv tool install vmware-aria
```

```bash
uv tool install vmware-avi
```

--------------------------------

### Deploy Linked Clone or from ISO

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/cli-reference.md

Deploy a linked clone from a source VM and snapshot, or deploy a VM by attaching an ISO image.

```bash
vmware-aiops deploy linked-clone --source <vm> --snapshot <snap> --name <new-name>
```

```bash
vmware-aiops deploy iso <vm-name> --iso "[datastore] path/file.iso"
```

--------------------------------

### Install Ollama on macOS

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Install Ollama on macOS using Homebrew. Ollama is required for running local AI models.

```bash
# macOS
brew install ollama
```

--------------------------------

### Deploy VM from OVA or Template

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/cli-reference.md

Deploy a virtual machine from an OVA file or a VM template. Optional datastore and network can be specified.

```bash
vmware-aiops deploy ova <path> --name <vm-name> [--datastore <ds>] [--network <net>]
```

```bash
vmware-aiops deploy template <template-name> --name <vm-name> [--datastore <ds>]
```

--------------------------------

### Verify vmware-aiops setup

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/localcowork.md

Runs the vmware-aiops doctor command to check if the setup and configuration are correct. This is a crucial step before integrating with other tools.

```bash
vmware-aiops doctor
```

--------------------------------

### Update VMware AI Ops Installation

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Re-run the install command for your specific channel to update to the latest version of VMware AI Ops.

```bash
clawhub install vmware-aiops
```

```bash
npx skills add zw008/VMware-AIops
```

```bash
/plugin marketplace add zw008/VMware-AIops
```

```bash
cd VMware-AIops && git pull origin main && uv pip install -e .
```

```bash
uv tool install vmware-aiops --force
```

--------------------------------

### Browse Datastore Files

Source: https://context7.com/zw008/vmware-aiops/llms.txt

Navigate datastore file systems and scan for deployable image formats.

```bash
# Browse datastore root
vmware-aiops datastore browse datastore1

# Browse specific subdirectory
vmware-aiops datastore browse datastore1 --path "iso/"

# Browse with pattern filter
vmware-aiops datastore browse datastore1 --pattern "*.ova"

# Scan all datastores for deployable images
vmware-aiops datastore scan-images --target prod-vcenter
```

--------------------------------

### Create VM Creation Plan

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Initiates the creation of a plan for batch VM operations, including cloning and reconfiguration.

```bash
vm_create_plan
```

--------------------------------

### Manage VM Snapshots

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/cli-reference.md

Create, list, revert, and delete snapshots for a virtual machine. Snapshots require a name.

```bash
vmware-aiops vm snapshot-create <vm-name> --name <snap-name>
```

```bash
vmware-aiops vm snapshot-list <vm-name>
```

```bash
vmware-aiops vm snapshot-revert <vm-name> --name <snap-name>
```

```bash
vmware-aiops vm snapshot-delete <vm-name> --name <snap-name>
```

--------------------------------

### Get Cluster Information

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/cli-reference.md

Retrieve information about a specific cluster by its name.

```bash
vmware-aiops cluster info <name>
```

--------------------------------

### VM Deployment and Provisioning

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/capabilities.md

Commands for deploying virtual machines from templates, OVAs, or cloning existing VMs.

```APIDOC
## VM Deployment

### Commands
- **Deploy from OVA**: `deploy ova <path> --name <vm>`
- **Deploy from Template**: `deploy template <tmpl> --name <vm>`
- **Linked Clone**: `deploy linked-clone --source <vm> --snapshot <snap> --name <new>`
- **Attach ISO**: `deploy iso <vm> --iso "[ds] path/to.iso"`
- **Convert to Template**: `deploy mark-template <vm>`
- **Batch Clone**: `deploy batch-clone --source <vm> --count <n>`
- **Batch Deploy**: `deploy batch spec.yaml`
```

--------------------------------

### Create, Delete, and Reconfigure VMs

Source: https://context7.com/zw008/vmware-aiops/llms.txt

Commands for provisioning new VMs and modifying existing resource allocations.

```bash
# Create a new VM with 4 CPUs, 8GB RAM, 100GB disk
vmware-aiops vm create my-new-vm --cpu 4 --memory 8192 --disk 100 --target lab-esxi

# Delete a VM (requires double confirmation)
vmware-aiops vm delete my-old-vm

# Reconfigure existing VM resources (requires double confirmation)
vmware-aiops vm reconfigure my-vm --cpu 8 --memory 16384
```

--------------------------------

### Create Baseline Snapshot for VM

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Creates a baseline snapshot for a virtual machine. Specify the VM name and the desired snapshot name.

```bash
vmware-aiops vm snapshot-create lab-vm --name baseline
```

--------------------------------

### Check Python Version

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Verify that Python version 3.10 or higher is installed, which is a prerequisite for the Python backend.

```bash
python3 --version
```

--------------------------------

### Plan/Apply Tools

Source: https://context7.com/zw008/vmware-aiops/llms.txt

Tools for creating, applying, rolling back, and listing deployment plans.

```APIDOC
## Plan/Apply Tools

### Description
Tools for creating, applying, rolling back, and listing deployment plans.

### Tools
- **vm_create_plan**(operations: list[dict], target: str = None) -> dict
- **vm_apply_plan**(plan_id: str, target: str = None) -> dict
- **vm_rollback_plan**(plan_id: str, target: str = None) -> dict
- **vm_list_plans**() -> list[dict]
```

--------------------------------

### Run Aider with VMware-AIops

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Installation and execution commands for Aider, including support for local models via Ollama.

```bash
# Install Aider
pip install aider-chat

# Install Ollama for local models (optional)
# macOS:
brew install ollama
ollama pull qwen2.5-coder:32b

# Run with cloud API
aider --conventions codex-skill/AGENTS.md

# Or with local model via Ollama
aider --conventions codex-skill/AGENTS.md \
  --model ollama/qwen2.5-coder:32b
```

--------------------------------

### Automated health check in an agent workflow

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/mcp-agent.md

Example of initializing an MCPApp and using an agent to query infrastructure health.

```python
# agent_script.py
from mcp_agent.app import MCPApp
from mcp_agent.agents.agent import Agent
from mcp_agent.workflows.orchestrator.orchestrator import Orchestrator

app = MCPApp(name="vmware-health-check")

async with app.run() as vmware_app:
    agent = Agent(
        name="vmware-ops",
        instruction="You manage VMware infrastructure. Check health and report issues.",
        server_names=["vmware-aiops"],
    )
    async with agent:
        result = await agent.send("Get all active alarms and summarize by severity")
        print(result)
```

--------------------------------

### Run Aider with Low-Memory Local Qwen Model

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Configure Aider to use the lower-memory Qwen 2.5 Coder 7B model served by Ollama for systems with limited resources.

```bash
# Low-memory option

  --model ollama/qwen2.5-coder:7b
```

--------------------------------

### Check Current VMware AI Ops Version

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Command to check the currently installed version of VMware AI Ops.

```bash
vmware-aiops --version
```

--------------------------------

### Upload and Download Files in VM Guest OS

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/cli-reference.md

Upload local files to the guest OS or download files from the guest OS. Requires VMware Tools and specifying the user.

```bash
vmware-aiops vm guest-upload <vm-name> --local ./script.sh --guest /tmp/script.sh --user root
```

```bash
vmware-aiops vm guest-download <vm-name> --guest /var/log/syslog --local ./syslog.txt --user root
```

--------------------------------

### Check Node.js Version

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Verify that Node.js version 18 or higher is installed, required for Gemini CLI and Codex CLI.

```bash
node --version
```

--------------------------------

### Deploy VM from Template

Source: https://context7.com/zw008/vmware-aiops/llms.txt

Clones a virtual machine from an existing vSphere template. Allows overriding CPU and memory resources.

```bash
# Deploy from template
vmware-aiops deploy template golden-ubuntu --name new-dev-vm
```

```bash
# Deploy with custom resources
vmware-aiops deploy template golden-ubuntu \
  --name new-dev-vm \
  --datastore datastore1 \
  --cpu 8 \
  --memory 16384
```

--------------------------------

### Deployment Tools

Source: https://context7.com/zw008/vmware-aiops/llms.txt

Tools for deploying virtual machines from OVA images, templates, and linked clones, as well as managing ISO attachments and VM conversions.

```APIDOC
## Deployment Tools

### Description
Tools for deploying virtual machines from OVA images, templates, and linked clones, as well as managing ISO attachments and VM conversions.

### Tools
- **deploy_vm_from_ova**(ova_path: str, vm_name: str, datastore_name: str, ...) -> str
- **deploy_vm_from_template**(template_name: str, new_name: str, ...) -> str
- **deploy_linked_clone**(source_vm_name: str, snapshot_name: str, new_name: str, ...) -> str
- **attach_iso_to_vm**(vm_name: str, iso_ds_path: str, target: str = None) -> str
- **convert_vm_to_template**(vm_name: str, target: str = None) -> str
- **batch_clone_vms**(source_vm_name: str, vm_names: list[str], ...) -> list[dict]
- **batch_linked_clone_vms**(source_vm_name: str, snapshot_name: str, vm_names: list[str], ...) -> list[dict]
- **batch_deploy_from_spec**(spec_path: str, target: str = None) -> list[dict]
```

--------------------------------

### Configure Continue CLI for Qwen

Source: https://github.com/zw008/vmware-aiops/blob/main/README.md

Configure the Continue CLI to use Qwen models by specifying the provider, API base, API key, and model name in the config file.

```yaml
# Qwen
models:
  - name: qwen-coder
    provider: openai-compatible
    apiBase: https://dashscope.aliyuncs.com/compatible-mode/v1
    apiKey: your-dashscope-key
    model: qwen-coder-plus-latest
```

--------------------------------

### Manage Daemon Service

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/cli-reference.md

Control the status of the AIOPs daemon service. Commands include start, stop, and status checks.

```bash
vmware-aiops daemon start
```

```bash
vmware-aiops daemon stop
```

```bash
vmware-aiops daemon status
```

--------------------------------

### List Plans

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/references/cli-reference.md

List available plans for multi-step operations.

```bash
vmware-aiops plan list
```

--------------------------------

### Execute Multi-Step VM Operations

Source: https://context7.com/zw008/vmware-aiops/llms.txt

Use the vm_create_plan function to define a sequence of VM actions, then apply or rollback the plan as needed.

```python
# MCP Tool: vm_create_plan
# Create a plan for multi-step operations

operations = [
    {"action": "power_off", "vm_name": "test-1"},
    {"action": "revert_snapshot", "vm_name": "test-1", "snapshot_name": "baseline"},
    {"action": "power_on", "vm_name": "test-1"},
    {"action": "power_off", "vm_name": "test-2"},
    {"action": "revert_snapshot", "vm_name": "test-2", "snapshot_name": "baseline"},
    {"action": "power_on", "vm_name": "test-2"},
]

plan = vm_create_plan(operations=operations, target="prod-vcenter")
# Returns: {"plan_id": "abc123", "steps": [...], "summary": {"vms_affected": 2, "irreversible_steps": 0, "rollback_available": true}}

# Apply the plan after user confirmation
result = vm_apply_plan(plan_id="abc123")
# Returns: {"status": "success", "completed_steps": 6}

# If plan fails, rollback executed steps
rollback_result = vm_rollback_plan(plan_id="abc123")
# Returns: {"status": "rolled_back", "reversed_steps": 3, "skipped_steps": 0}

# List all pending/failed plans
plans = vm_list_plans()
# Returns: [{"plan_id": "abc123", "status": "pending", "steps": 6, "created_at": "..."}]
```

--------------------------------

### Execute Command Inside VM

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Executes a command within a virtual machine. Requires VMware Tools to be installed. Specify the VM name, command, arguments, and user.

```bash
vmware-aiops vm guest-exec <name> --cmd /bin/bash --args "-c 'whoami'" --user root
```

--------------------------------

### Plan and Apply Management Tools

Source: https://context7.com/zw008/vmware-aiops/llms.txt

Functions for creating, applying, and rolling back execution plans.

```python
vm_create_plan(operations: list[dict], target: str = None) -> dict
```

```python
vm_apply_plan(plan_id: str, target: str = None) -> dict
```

```python
vm_rollback_plan(plan_id: str, target: str = None) -> dict
```

```python
vm_list_plans() -> list[dict]
```

--------------------------------

### Deploy VM from OVA

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Deploys a virtual machine from an OVA file. Specify the OVA path, VM name, and datastore.

```bash
vmware-aiops deploy ova <path> --name <vm> --datastore <ds>
```

--------------------------------

### Transfer Files to/from VM Guest

Source: https://context7.com/zw008/vmware-aiops/llms.txt

Uploads or downloads files between the local machine and a virtual machine using VMware Tools. Requires VMware Tools to be installed and running.

```bash
# Upload file to VM
vmware-aiops vm guest-upload my-vm \
  --local ./script.sh \
  --guest /tmp/script.sh \
  --user root
```

```bash
# Download file from VM
vmware-aiops vm guest-download my-vm \
  --guest /var/log/syslog \
  --local ./syslog.txt \
  --user root
```

--------------------------------

### Configure Goose interactively

Source: https://github.com/zw008/vmware-aiops/blob/main/docs/integrations/goose.md

Use the interactive configuration tool to add the MCP server.

```bash
goose configure
# Select: Add Extension → MCP Server
# Name: vmware-aiops
# Command: uvx --from vmware-aiops vmware-aiops-mcp
# Env: VMWARE_AIOPS_CONFIG=~/.vmware-aiops/config.yaml
```

--------------------------------

### Run MCP Server with Docker Compose

Source: https://github.com/zw008/vmware-aiops/blob/main/RELEASE_NOTES.md

Use this command to launch the MCP server without installing Python or a virtual environment. The configuration directory is mounted read-only into the container.

```bash
docker compose up -d
```

--------------------------------

### Deploy VM from OVA

Source: https://github.com/zw008/vmware-aiops/blob/main/skills/vmware-aiops/SKILL.md

Deploys a virtual machine from an OVA file. Requires specifying the OVA path, VM name, and target datastore.

```bash
vmware-aiops deploy ova ./image.ova --name lab-vm --datastore ds1
```
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