VMware-AIops
AI-powered VMware vCenter/ESXi monitoring and operations. 20 MCP tools for inventory queries, health monitoring, VM lifecycle management, fast provisioning (Linked Clone, OVA, template deploy), snapshot management, and datastore browsing. Supports vSphere 6.5–8.0. Works with local models via Ollama/LM Studio.
README
<!-- mcp-name: io.github.zw008/vmware-aiops -->
VMware AIops
English | 中文
AI-powered VMware vCenter/ESXi monitoring and operations tool.
Need read-only monitoring only? See VMware-Monitor — an independent repository with code-level safety (zero destructive code in the codebase).
Quick Install (Recommended)
Works with Claude Code, Cursor, Codex, Gemini CLI, Trae, and 30+ AI agents:
# Via Skills.sh
npx skills add zw008/VMware-AIops
# Via ClawHub
clawhub install vmware-aiops
Claude Code Plugin Install
# Add marketplace
/plugin marketplace add zw008/VMware-AIops
# Install plugin
/plugin install vmware-ops
# Use the skill
/vmware-ops:vmware-aiops
Capabilities Overview
Architecture
User (Natural Language)
↓
AI CLI Tool (Claude Code / Gemini / Codex / Aider / Continue / Trae / Kimi)
↓ reads SKILL.md / AGENTS.md / rules
↓
vmware-aiops CLI
↓ pyVmomi (vSphere SOAP API)
↓
vCenter Server ──→ ESXi Cluster ──→ VM
or
ESXi Standalone Host ──→ VM
Version Compatibility
| vSphere Version | Support | Notes |
|---|---|---|
| 8.0 / 8.0U1-U3 | ✅ Full | CreateSnapshot_Task deprecated → use CreateSnapshotEx_Task |
| 7.0 / 7.0U1-U3 | ✅ Full | All APIs supported |
| 6.7 | ✅ Compatible | Backward-compatible, tested |
| 6.5 | ✅ Compatible | Backward-compatible, tested |
pyVmomi auto-negotiates the API version during SOAP handshake — no manual configuration needed. The same codebase manages both 7.0 and 8.0 environments seamlessly.
1. Inventory
| Feature | vCenter | ESXi | Details |
|---|---|---|---|
| List VMs | ✅ | ✅ | Name, power state, CPU, memory, guest OS, IP |
| List Hosts | ✅ | ⚠️ Self only | CPU cores, memory, ESXi version, VM count, uptime |
| List Datastores | ✅ | ✅ | Capacity, free/used, type (VMFS/NFS), usage % |
| List Clusters | ✅ | ❌ | Host count, DRS/HA status |
| List Networks | ✅ | ✅ | Network name, associated VM count |
2. Health & Monitoring
| Feature | vCenter | ESXi | Details |
|---|---|---|---|
| Active Alarms | ✅ | ✅ | Severity, alarm name, entity, timestamp |
| Event/Log Query | ✅ | ✅ | Filter by time range (--hours), severity level; 50+ event types |
| Hardware Sensors | ✅ | ✅ | Temperature, voltage, fan status |
| Host Services | ✅ | ✅ | hostd, vpxa, etc. running/stopped |
Monitored Event Types:
| Category | Events |
|---|---|
| VM Failures | VmFailedToPowerOnEvent, VmDiskFailedEvent, VmFailoverFailed |
| Host Issues | HostConnectionLostEvent, HostShutdownEvent, HostIpChangedEvent |
| Storage | DatastoreCapacityIncreasedEvent, NASDatastoreEvent, SCSI high latency |
| HA/DRS | DasHostFailedEvent, DrsVmMigratedEvent, DrsSoftRuleViolationEvent |
| Auth | UserLoginSessionEvent, BadUsernameSessionEvent |
3. VM Lifecycle
| Operation | Command | Confirmation | vCenter | ESXi |
|---|---|---|---|---|
| Power On | vm power-on <name> |
— | ✅ | ✅ |
| Graceful Shutdown | vm power-off <name> |
Double | ✅ | ✅ |
| Force Power Off | vm power-off <name> --force |
Double | ✅ | ✅ |
| Reset | vm reset <name> |
— | ✅ | ✅ |
| Suspend | vm suspend <name> |
— | ✅ | ✅ |
| VM Info | vm info <name> |
— | ✅ | ✅ |
| Create VM | vm create <name> --cpu --memory --disk |
— | ✅ | ✅ |
| Delete VM | vm delete <name> |
Double | ✅ | ✅ |
| Reconfigure | vm reconfigure <name> --cpu --memory |
Double | ✅ | ✅ |
| Create Snapshot | vm snapshot-create <name> --name <snap> |
— | ✅ | ✅ |
| List Snapshots | vm snapshot-list <name> |
— | ✅ | ✅ |
| Revert Snapshot | vm snapshot-revert <name> --name <snap> |
— | ✅ | ✅ |
| Delete Snapshot | vm snapshot-delete <name> --name <snap> |
— | ✅ | ✅ |
| Clone VM | vm clone <name> --new-name <new> |
— | ✅ | ✅ |
| vMotion | vm migrate <name> --to-host <host> |
— | ✅ | ❌ |
4. VM Deployment & Provisioning
| Operation | Command | Speed | vCenter | ESXi |
|---|---|---|---|---|
| Deploy from OVA | deploy ova <path> --name <vm> |
Minutes | ✅ | ✅ |
| Deploy from Template | deploy template <tmpl> --name <vm> |
Minutes | ✅ | ✅ |
| Linked Clone | deploy linked-clone --source <vm> --snapshot <snap> --name <new> |
Seconds | ✅ | ✅ |
| Attach ISO | deploy iso <vm> --iso "[ds] path/to.iso" |
Instant | ✅ | ✅ |
| Convert to Template | deploy mark-template <vm> |
Instant | ✅ | ✅ |
| Batch Clone | deploy batch-clone --source <vm> --count <n> |
Minutes | ✅ | ✅ |
| Batch Deploy (YAML) | deploy batch spec.yaml |
Auto | ✅ | ✅ |
5. Datastore Browser
| Feature | vCenter | ESXi | Details |
|---|---|---|---|
| Browse Files | ✅ | ✅ | List files/folders in any datastore path |
| Scan Images | ✅ | ✅ | Discover ISO, OVA, OVF, VMDK across all datastores |
| Local Cache | ✅ | ✅ | Registry at ~/.vmware-aiops/image_registry.json |
6. Scheduled Scanning & Notifications
| Feature | Details |
|---|---|
| Daemon | APScheduler-based, configurable interval (default 15 min) |
| Multi-target Scan | Sequentially scan all configured vCenter/ESXi targets |
| Scan Content | Alarms + Events + Host logs (hostd, vmkernel, vpxd) |
| Log Analysis | Regex pattern matching: error, fail, critical, panic, timeout, corrupt |
| Structured Log | JSONL output to ~/.vmware-aiops/scan.log |
| Webhook | Slack, Discord, or any HTTP endpoint |
| Daemon Management | daemon start/stop/status, PID file, graceful shutdown |
7. Safety Features
| Feature | Details |
|---|---|
| Dry-Run Mode | --dry-run on any destructive command prints exact API calls without executing |
| Plan → Confirm → Execute → Log | Structured workflow: show current state, confirm changes, execute, audit log |
| Double Confirmation | All destructive ops (power-off, delete, reconfigure, snapshot-revert/delete, clone, migrate) require 2 sequential confirmations — no bypass flags |
| Rejection Logging | Declined confirmations are recorded in the audit trail |
| Audit Trail | All operations logged to ~/.vmware-aiops/audit.log (JSONL) with before/after state |
| Input Validation | VM name, CPU (1-128), memory (128-1048576 MB), disk (1-65536 GB) validated |
| Password Protection | .env file loading with permission check; never in shell history |
| SSL Self-signed Support | disableSslCertValidation — only for ESXi with self-signed certs in isolated labs; production should use CA-signed certificates |
| Prompt Injection Protection | vSphere event messages and host logs are truncated, stripped of control characters, and wrapped in boundary markers before output |
| Webhook Data Scope | Sends notifications to user-configured URLs only — no third-party services by default |
| Task Waiting | All async operations wait for completion and report result |
| State Validation | Pre-operation checks (VM exists, power state correct) |
8. vSAN Management
| Feature | Details |
|---|---|
| Health Check | Cluster-wide health summary, per-group test results |
| Capacity | Total/free/used capacity with projections |
| Disk Groups | Cache SSD + capacity disks per host |
| Performance | IOPS, latency, throughput per cluster/host/VM |
Requires pyVmomi 8.0.3+ (vSAN SDK merged). For older versions, install the standalone vSAN Management SDK.
9. Aria Operations / VCF Operations
| Feature | Details |
|---|---|
| Historical Metrics | Time-series CPU, memory, disk, network with months of history |
| Anomaly Detection | ML-based dynamic baselines and anomaly alerts |
| Capacity Planning | What-if analysis, time-to-exhaustion, forecasting |
| Right-sizing | CPU/memory recommendations per VM |
| Intelligent Alerts | Root cause analysis, remediation recommendations |
REST API at
/suite-api/. Auth:vRealizeOpsToken. Rebranded as VCF Operations in VCF 9.0.
10. vSphere Kubernetes Service (VKS)
| Feature | Details |
|---|---|
| List Clusters | Tanzu Kubernetes clusters with phase status |
| Cluster Health | InfrastructureReady, ControlPlaneAvailable, WorkersAvailable conditions |
| Scale Workers | Adjust MachineDeployment replicas |
| Node Status | Machine status, ready/unhealthy counts |
Kubernetes-native API via kubectl/kubeconfig. VKS 3.6+ uses Cluster API specification.
11. vCenter vs ESXi Comparison
| Capability | vCenter | ESXi Standalone |
|---|---|---|
| Full cluster inventory | ✅ | ❌ Single host only |
| DRS/HA management | ✅ | ❌ |
| vMotion migration | ✅ | ❌ |
| Cross-host clone | ✅ | ❌ |
| All VM lifecycle ops | ✅ | ✅ |
| OVA/Template/Linked Clone deploy | ✅ | ✅ |
| Datastore browsing & image scan | ✅ | ✅ |
| Alarms & events | ✅ | ✅ |
| Hardware sensors | ✅ | ✅ |
| Host services | ✅ | ✅ |
| Snapshots | ✅ | ✅ |
| Scheduled scanning | ✅ | ✅ |
Supported AI Platforms
| Platform | Status | Config File | AI Model |
|---|---|---|---|
| Claude Code | ✅ Native Skill | skills/vmware-aiops/SKILL.md |
Anthropic Claude |
| Gemini CLI | ✅ Extension | gemini-extension/GEMINI.md |
Google Gemini |
| OpenAI Codex CLI | ✅ Skill + AGENTS.md | codex-skill/AGENTS.md |
OpenAI GPT |
| Aider | ✅ Conventions | codex-skill/AGENTS.md |
Any (cloud + local) |
| Continue CLI | ✅ Rules | codex-skill/AGENTS.md |
Any (cloud + local) |
| Trae IDE | ✅ Rules | trae-rules/project_rules.md |
Claude/DeepSeek/GPT-4o/Doubao |
| Kimi Code CLI | ✅ Skill | kimi-skill/SKILL.md |
Moonshot Kimi |
| MCP Server | ✅ MCP Protocol | mcp_server/ |
Any MCP client |
| Python CLI | ✅ Standalone | N/A | N/A |
Platform Comparison
| Feature | Claude Code | Gemini CLI | Codex CLI | Aider | Continue | Trae IDE | Kimi CLI |
|---|---|---|---|---|---|---|---|
| Cloud AI | Anthropic | OpenAI | Any | Any | Multi | Moonshot | |
| Local models | — | — | — | Ollama | Ollama | — | — |
| Skill system | SKILL.md | Extension | SKILL.md | — | Rules | Rules | SKILL.md |
| MCP support | Native | Native | Via Skills | Third-party | Native | — | — |
| Free tier | — | 60 req/min | — | Self-hosted | Self-hosted | — | — |
MCP Server Integrations
The vmware-aiops MCP server works with any MCP-compatible agent or tool. Ready-to-use configuration templates are in examples/mcp-configs/.
| Agent / Tool | Local Model Support | Config Template |
|---|---|---|
| Goose | ✅ Ollama, LM Studio | goose.json |
| LocalCowork | ✅ Fully offline | localcowork.json |
| mcp-agent | ✅ Ollama, vLLM | mcp-agent.yaml |
| VS Code Copilot | — | .vscode/mcp.json |
| Cursor | — | cursor.json |
| Continue | ✅ Ollama | continue.yaml |
| Claude Code | — | claude-code.json |
Fully local operation (no cloud API required):
# Aider + Ollama + vmware-aiops (via AGENTS.md)
aider --conventions codex-skill/AGENTS.md --model ollama/qwen2.5-coder:32b
# Any MCP agent + local model + vmware-aiops MCP server
# See examples/mcp-configs/ for your agent's config format
Installation
Step 0: Prerequisites
# Python 3.10+ required
python3 --version
# Node.js 18+ required for Gemini CLI and Codex CLI
node --version
Step 1: Clone & Install Python Backend
All platforms share the same Python backend.
git clone https://github.com/zw008/VMware-AIops.git
cd VMware-AIops
python3 -m venv .venv
source .venv/bin/activate
pip install -e .
Step 2: Configure
mkdir -p ~/.vmware-aiops
cp config.example.yaml ~/.vmware-aiops/config.yaml
# Edit config.yaml with your vCenter/ESXi targets
Set passwords via .env file (recommended):
# Use the template
cp .env.example ~/.vmware-aiops/.env
# Edit and fill in your passwords, then lock permissions
chmod 600 ~/.vmware-aiops/.env
Security note: Prefer
.envfile over command-lineexportto avoid passwords appearing in shell history. The.envfile should havechmod 600(owner-only read/write).
Password environment variable naming convention:
VMWARE_{TARGET_NAME_UPPER}_PASSWORD
# Replace hyphens with underscores, UPPERCASE
# Example: target "home-esxi" → VMWARE_HOME_ESXI_PASSWORD
# Example: target "prod-vcenter" → VMWARE_PROD_VCENTER_PASSWORD
Security Best Practices
- NEVER hardcode passwords in scripts or config files
- NEVER pass passwords as command-line arguments (visible in
ps) - ALWAYS use
~/.vmware-aiops/.envwithchmod 600 - ALWAYS configure connections via
config.yaml— credentials are loaded from.envautomatically - Config File Contents:
config.yamlstores target hostnames, ports, and a reference to the.envfile. It does not contain passwords or tokens. All secrets are stored exclusively in.env - TLS: Enabled by default. Disable only for ESXi hosts with self-signed certificates in isolated lab environments
- Webhook: Disabled by default. When enabled, sends monitoring summaries to your own configured URL only — payloads contain no credentials, IPs, or PII, only aggregated alert metadata. No data sent to third-party services
- Least Privilege: Use a dedicated vCenter service account with minimal permissions. For monitoring-only use cases, prefer the read-only VMware-Monitor
- Prompt Injection Protection: All vSphere-sourced content is truncated, stripped of control characters, and wrapped in boundary markers before output
- Code Review: We recommend reviewing the source code and commit history before deploying in production
Step 3: Connect Your AI Tool
Choose one (or more) of the following:
Option A: Claude Code (Marketplace)
Method 1: Marketplace (recommended)
In Claude Code, run:
/plugin marketplace add zw008/VMware-AIops
/plugin install vmware-ops
Then use:
/vmware-ops:vmware-aiops
> Show me all VMs on esxi-lab.example.com
Method 2: Local install
# 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))
"
Restart Claude Code, then:
/vmware-ops:vmware-aiops
Submit to Official Marketplace
This plugin can also be submitted to the Anthropic official plugin directory for public discovery.
Option B: Gemini CLI
# 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
Then start Gemini CLI:
gemini
> Show me all VMs on my ESXi host
Option C: OpenAI Codex CLI
# 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
Then start Codex CLI:
codex --enable skills
> List all VMs on my ESXi
Option D: Aider (supports local models)
# 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
Option E: Continue CLI (supports local models)
# 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
Configure ~/.continue/config.yaml for local model:
models:
- name: local-coder
provider: ollama
model: qwen2.5-coder:32b
Then:
cn
> Check ESXi health and alarms
Option F: Trae IDE
Copy the rules file to your project's .trae/rules/ directory:
mkdir -p .trae/rules
cp trae-rules/project_rules.md .trae/rules/project_rules.md
Trae IDE's Builder Mode reads .trae/rules/ Markdown files at startup.
Note: You can also install Claude Code extension in Trae IDE and use
.claude/skills/format directly.
Option G: Kimi Code CLI
# Copy skill file to Kimi skills directory
mkdir -p ~/.kimi/skills/vmware-aiops
cp kimi-skill/SKILL.md ~/.kimi/skills/vmware-aiops/SKILL.md
Option H: MCP Server (Smithery / Glama / Claude Desktop)
The MCP server exposes VMware operations as tools via the Model Context Protocol. Works with any MCP-compatible client (Claude Desktop, Cursor, etc.).
# Run directly
python -m mcp_server
# Or via the installed entry point
vmware-aiops-mcp
# With a custom config path
VMWARE_AIOPS_CONFIG=/path/to/config.yaml python -m mcp_server
Claude Desktop config (claude_desktop_config.json):
{
"mcpServers": {
"vmware-aiops": {
"command": "python",
"args": ["-m", "mcp_server"],
"env": {
"VMWARE_AIOPS_CONFIG": "/path/to/config.yaml"
}
}
}
}
Install via Smithery:
npx -y @smithery/cli install @zw008/VMware-AIops --client claude
Option I: Standalone CLI (no AI)
# Already installed in Step 1
source .venv/bin/activate
vmware-aiops inventory vms --target home-esxi
vmware-aiops health alarms --target home-esxi
vmware-aiops vm power-on my-vm --target home-esxi
Update / Upgrade
Already installed? Re-run the install command for your channel to get the latest version:
| Install Channel | Update Command |
|---|---|
| ClawHub | clawhub install vmware-aiops |
| Skills.sh | npx skills add zw008/VMware-AIops |
| Claude Code Plugin | /plugin marketplace add zw008/VMware-AIops |
| Git clone | cd VMware-AIops && git pull origin main && uv pip install -e . |
| uv | uv tool install vmware-aiops --force |
Check your current version: vmware-aiops --version
Chinese Cloud Models
For users in China who prefer domestic cloud APIs or have limited access to overseas services.
DeepSeek
Cost-effective, strong coding capability.
# Set DeepSeek API key (get from https://platform.deepseek.com)
export DEEPSEEK_API_KEY="your-key"
# Run with Aider
aider --conventions codex-skill/AGENTS.md \
--model deepseek/deepseek-coder
Persistent config ~/.aider.conf.yml:
model: deepseek/deepseek-coder
conventions: codex-skill/AGENTS.md
Qwen (Alibaba Cloud)
Alibaba Cloud's coding model, free tier available.
# Set DashScope API key (get from https://dashscope.console.aliyun.com)
export DASHSCOPE_API_KEY="your-key"
aider --conventions codex-skill/AGENTS.md \
--model qwen/qwen-coder-plus
Or via OpenAI-compatible endpoint:
export OPENAI_API_BASE="https://dashscope.aliyuncs.com/compatible-mode/v1"
export OPENAI_API_KEY="your-dashscope-key"
aider --conventions codex-skill/AGENTS.md \
--model qwen-coder-plus-latest
Doubao (ByteDance)
export OPENAI_API_BASE="https://ark.cn-beijing.volces.com/api/v3"
export OPENAI_API_KEY="your-ark-key"
aider --conventions codex-skill/AGENTS.md \
--model your-doubao-endpoint-id
With Continue CLI
Configure ~/.continue/config.yaml:
# DeepSeek
models:
- name: deepseek-coder
provider: openai-compatible
apiBase: https://api.deepseek.com/v1
apiKey: your-deepseek-key
model: deepseek-coder
# 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
Local Models (Aider + Ollama)
For fully offline operation — no cloud API, no internet, full privacy.
Aider + Ollama + local Qwen/DeepSeek is ideal for air-gapped environments.
Step 1: Install Ollama
# macOS
brew install ollama
# Linux — download from https://ollama.com/download and install manually
# See https://github.com/ollama/ollama for platform-specific instructions
Step 2: Pull a model
| Model | Command | Size | Note |
|---|---|---|---|
| Qwen 2.5 Coder 32B | ollama pull qwen2.5-coder:32b |
~20GB | Best local coding model |
| Qwen 2.5 Coder 7B | ollama pull qwen2.5-coder:7b |
~4.5GB | Low-memory option |
| DeepSeek Coder V2 | ollama pull deepseek-coder-v2 |
~8.9GB | Strong reasoning |
| CodeLlama 34B | ollama pull codellama:34b |
~19GB | Meta coding model |
Hardware: 32B → ~20GB VRAM (or 32GB RAM for CPU). 7B → 8GB RAM.
Step 3: Run with Aider
pip install aider-chat
ollama serve
# Aider + local Qwen (recommended)
aider --conventions codex-skill/AGENTS.md \
--model ollama/qwen2.5-coder:32b
# Aider + local DeepSeek
aider --conventions codex-skill/AGENTS.md \
--model ollama/deepseek-coder-v2
# Low-memory option
aider --conventions codex-skill/AGENTS.md \
--model ollama/qwen2.5-coder:7b
Persistent config ~/.aider.conf.yml:
model: ollama/qwen2.5-coder:32b
conventions: codex-skill/AGENTS.md
Local Architecture
User → Aider CLI → Ollama (localhost:11434) → Qwen / DeepSeek local model
│ ↓
│ reads AGENTS.md instructions
│ ↓
└──────────────────────────────→ vmware-aiops CLI ──→ ESXi / vCenter
Tip: Local models are fully offline — perfect for air-gapped environments or strict data compliance.
CLI Reference
# Inventory
vmware-aiops inventory vms # List VMs
vmware-aiops inventory hosts --target prod-vcenter # List hosts
vmware-aiops inventory datastores # List datastores
vmware-aiops inventory clusters # List clusters
# Health
vmware-aiops health alarms # Active alarms
vmware-aiops health events --hours 24 --severity warning # Recent events
# VM operations
vmware-aiops vm info my-vm # VM details
vmware-aiops vm power-on my-vm # Power on
vmware-aiops vm power-off my-vm # Graceful shutdown (2x confirm)
vmware-aiops vm power-off my-vm --force # Force power off (2x confirm)
vmware-aiops vm create my-new-vm --cpu 4 --memory 8192 --disk 100 # Create VM
vmware-aiops vm delete my-vm --confirm # Delete VM (2x confirm)
vmware-aiops vm reconfigure my-vm --cpu 4 --memory 8192 # Reconfigure (2x confirm)
vmware-aiops vm snapshot-create my-vm --name "before-upgrade" # Create snapshot
vmware-aiops vm snapshot-list my-vm # List snapshots
vmware-aiops vm snapshot-revert my-vm --name "before-upgrade" # Revert snapshot
vmware-aiops vm snapshot-delete my-vm --name "before-upgrade" # Delete snapshot
vmware-aiops vm clone my-vm --new-name my-vm-clone # Clone VM
vmware-aiops vm migrate my-vm --to-host esxi-02 # vMotion
# Deploy
vmware-aiops deploy ova ./ubuntu.ova --name my-vm --datastore ds1 # Deploy from OVA
vmware-aiops deploy template golden-ubuntu --name new-vm # Deploy from template
vmware-aiops deploy linked-clone --source base-vm --snapshot clean --name test-vm # Linked clone (seconds)
vmware-aiops deploy iso my-vm --iso "[datastore1] iso/ubuntu-22.04.iso" # Attach ISO
vmware-aiops deploy mark-template golden-vm # Convert VM to template
vmware-aiops deploy batch-clone --source base-vm --count 5 --prefix lab # Batch clone
vmware-aiops deploy batch deploy.yaml # Batch deploy from YAML spec
# Datastore
vmware-aiops datastore browse datastore1 --path "iso/" # Browse datastore
vmware-aiops datastore scan-images --target home-esxi # Scan all datastores for images
vmware-aiops datastore images --type iso # List cached images
# Scan
vmware-aiops scan now # One-time scan
# Daemon
vmware-aiops daemon start # Start scanner
vmware-aiops daemon status # Check status
vmware-aiops daemon stop # Stop daemon
# vSAN
vmware-aiops vsan health [--target prod-vcenter] # vSAN health
vmware-aiops vsan capacity [--target prod-vcenter] # vSAN capacity
vmware-aiops vsan disks [--target prod-vcenter] # Disk groups
vmware-aiops vsan performance [--hours 1] [--target prod-vcenter] # Performance
# Aria Operations / VCF Operations
vmware-aiops ops alerts [--severity critical] # Intelligent alerts
vmware-aiops ops metrics <resource-name> [--hours 24] # Time-series metrics
vmware-aiops ops recommendations [--target prod-vcenter] # Right-sizing
vmware-aiops ops capacity <cluster-name> # Capacity planning
# vSphere Kubernetes Service (VKS)
vmware-aiops vks clusters [--namespace default] # List K8s clusters
vmware-aiops vks health <cluster-name> # Cluster health
vmware-aiops vks scale <machine-deployment> --replicas <n> # Scale workers
vmware-aiops vks nodes <cluster-name> # Node status
Configuration
See config.example.yaml for all options.
| Section | Key | Default | Description |
|---|---|---|---|
| targets | name | — | Friendly name |
| targets | host | — | vCenter/ESXi hostname or IP |
| targets | type | vcenter | vcenter or esxi |
| targets | port | 443 | Connection port |
| targets | verify_ssl | false | SSL certificate verification |
| scanner | interval_minutes | 15 | Scan frequency |
| scanner | severity_threshold | warning | Min severity: critical/warning/info |
| scanner | lookback_hours | 1 | How far back to scan |
| scanner | log_types | [vpxd, hostd, vmkernel] | Log sources |
| notify | log_file | ~/.vmware-aiops/scan.log | JSONL log output |
| notify | webhook_url | — | Webhook endpoint (Slack, Discord, etc.) |
Project Structure
VMware-AIops/
├── .claude-plugin/ # Claude Code marketplace manifest
│ └── marketplace.json
├── plugins/ # Claude Code plugin
│ └── vmware-ops/
│ ├── .claude-plugin/
│ │ └── plugin.json
│ └── skills/
│ └── vmware-aiops/
│ └── SKILL.md # Full operations skill
├── skills/ # Skills index (npx skills add)
│ └── vmware-aiops/
│ └── SKILL.md
├── vmware_aiops/ # Python backend
│ ├── config.py # YAML + .env config
│ ├── connection.py # Multi-target pyVmomi
│ ├── cli.py # Typer CLI (double confirm)
│ ├── ops/ # Operations
│ │ ├── inventory.py # VMs, hosts, datastores, clusters
│ │ ├── health.py # Alarms, events, sensors
│ │ ├── vm_lifecycle.py # VM CRUD, snapshots, clone, migrate
│ │ ├── vm_deploy.py # OVA, template, linked clone, batch deploy
│ │ └── datastore_browser.py # Datastore browsing, image discovery
│ ├── scanner/ # Log scanning daemon
│ └── notify/ # Notifications (JSONL + webhook)
├── gemini-extension/ # Gemini CLI extension
│ ├── gemini-extension.json
│ └── GEMINI.md
├── codex-skill/ # Codex + Aider + Continue
│ ├── SKILL.md
│ └── AGENTS.md
├── trae-rules/ # Trae IDE rules
│ └── project_rules.md
├── kimi-skill/ # Kimi Code CLI skill
│ └── SKILL.md
├── mcp_server/ # MCP server wrapper
│ ├── server.py # FastMCP server with tools
│ └── __main__.py
├── smithery.yaml # Smithery marketplace config
├── RELEASE_NOTES.md
├── config.example.yaml
└── pyproject.toml
API Coverage
Built on pyVmomi (vSphere Web Services API / SOAP).
| API Object | Usage |
|---|---|
vim.VirtualMachine |
VM lifecycle, snapshots, clone, migrate |
vim.HostSystem |
ESXi host info, sensors, services |
vim.Datastore |
Storage capacity, type, accessibility |
vim.host.DatastoreBrowser |
File browsing, image discovery (ISO/OVA/VMDK) |
vim.OvfManager |
OVA import and deployment |
vim.ClusterComputeResource |
Cluster, DRS, HA |
vim.Network |
Network listing |
vim.alarm.AlarmManager |
Active alarm monitoring |
vim.event.EventManager |
Event/log queries |
Related Projects
| Project | Description | Install |
|---|---|---|
| VMware-Monitor | Read-only monitoring — code-level enforced safety, zero destructive operations | clawhub install vmware-monitor |
| VMware-AIops (this repo) | Full AI-powered operations — monitoring + VM lifecycle management | clawhub install vmware-aiops |
Choosing between them: Use VMware-Monitor if you only need read-only monitoring with zero risk of accidental changes. Use VMware-AIops if you need full operations (create, delete, power, snapshot, clone, migrate).
Troubleshooting & Contributing
If you encounter any errors or issues, please send the error message, logs, or screenshots to zhouwei008@gmail.com. Contributions are welcome — feel free to join us in maintaining and improving this project!
License
MIT
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