vmware-privateai

Use this skill whenever the user needs the GPU / AI-infrastructure layer of VMware Private AI Foundation with NVIDIA (PAIF-N) on vSphere 9.x / VCF 9.1: inventory GPU hosts and physical GPU devices, see which VMs consume a vGPU and the profile each holds, read real-time GPU utilization, list the vGPU and DirectPath profile catalog, assign a VM's vGPU profile, and list Private AI Service (PAIS) served models and knowledge bases. Always use this skill for "list GPU hosts", "which VMs are using a vGPU", "GPU utilization", "assign a vGPU profile", "list vGPU profiles", "list served models" when the context is explicitly VMware / vSphere / VCF Private AI / NVIDIA vGPU. Do NOT use for the backing VM's power/snapshot/clone/migrate (use vmware-aiops), read-only vSphere inventory/alarms/host health (use vmware-monitor), or GPU-enabled Tanzu Kubernetes (use vmware-vks). This skill is the GPU lens; vmware-aiops owns the VM lifecycle behind it.

VMware Private AI (Foundation with NVIDIA) — GPU & Model-Serving Ops

Disclaimer: Community-maintained open-source project, not affiliated with, endorsed by, or sponsored by VMware, Inc., Broadcom Inc., or NVIDIA Corporation. "VMware", "vSphere", and "VCF" are trademarks of Broadcom; "NVIDIA" and "vGPU" are trademarks of NVIDIA. Source is publicly auditable under the MIT license.

The GPU / AI-infrastructure lens for the VMware skill family — GPU host & device inventory, vGPU consumers, real-time GPU utilization, the vGPU / DirectPath profile catalog, vGPU assignment, and Private AI Service (PAIS) served models and knowledge bases — over the vSphere 9.x / VCF 9.1 Web Services API (pyVmomi) plus the PAIS REST API.

Companion skills: vmware-aiops (the vCenter VMs behind AI workloads — power/snapshot/clone), vmware-vks (GPU-enabled Tanzu Kubernetes), vmware-monitor (read-only vSphere health).

Status: v1.0.1 — still beta in substance. Skill #15 of the family. The jump from 0.2.x to 1.0.1 is a distribution fix, not a maturity claim: the withdrawn first release used 1.0.0, and ClawHub resolves latest by version order, so every 0.x release was invisible there. The beta caveats below all still stand. Every API path is verified against official Broadcom/NVIDIA sources before use (tests/eval/spec/privateai_endpoints.py) — no endpoints written from memory. GET-response field names and the exact PAIS paths are defensive and pending validation against live 9.x hardware (see Troubleshooting). Governed by the family harness (audit + policy + teaching errors); read-vs-write authorization is delegated to the vCenter service account's RBAC role.

What This Skill Does

Category	Tools	Count	Read/Write
GPU inventory	host list/get, device list, vGPU consumer list	4	4 R
GPU utilization	real-time per-vGPU-VM utilization (gpu %, mem %, temp)	1	1 R
GPU readiness	per-host vGPU/PAIS readiness verdict + blocking reasons	1	1 R
Profile catalog	vGPU profile list, DirectPath profile list	2	2 R
Profile validation	pre-flight a vGPU profile change (power state + host offers it)	1	1 R
vGPU assignment	set a VM's vGPU profile (VM must be powered off)	1	1 W
Private AI Service	served-model list, model catalog, knowledge-base list, data-source list	4	4 R
PAIS monitoring	fleet GPU rollup (util/mem/temp, hot/idle, busiest)	1	1 R
Sizing & air-gap	LLM GPU/storage sizing advisor, local pais.yml image inspector	2	2 R

17 MCP tools (16 read / 1 write). Reads are strictly non-destructive. The single write (vgpu_assign) previews its blast radius, refuses a powered-on VM, never powers a VM off itself, is double-confirmed at the CLI, and is audit-logged. Pre-flight the write with vgpu_profile_validate.

Quick Install

bash

uv tool install vmware-privateai==1.4.0
vmware-privateai version
vmware-privateai gpu host-list        # first read — lists hosts that have a GPU

Config lives in ~/.vmware-privateai/config.yaml (targets + optional pais: section); passwords and the PAIS bearer token live in ~/.vmware-privateai/.env (chmod 600). See references/setup-guide.md.

When to Use This Skill

Use vmware-privateai for the GPU / AI-infrastructure layer: which hosts and physical devices have GPUs, which VMs hold a vGPU and what profile, real-time GPU utilization, the assignable vGPU / DirectPath profile catalog, changing a VM's vGPU profile, and the models / knowledge bases served by Private AI Service — when the context is explicitly VMware / vSphere / VCF Private AI / NVIDIA vGPU.

Do NOT use when: the task is the backing VM's lifecycle — power on/off, snapshot, clone, migrate, reconfigure CPU/RAM (→ vmware-aiops); read-only vSphere inventory, alarms, or host health (→ vmware-monitor); or GPU-enabled Tanzu Kubernetes / Supervisor namespaces (→ vmware-vks). vgpu_assign deliberately does not power the VM off — that is vmware-aiops's job, kept separate so this skill's blast radius stays "one VM, when it is already off".

Related Skills — Skill Routing

The user wants…	Skill
Inventory GPUs / vGPU consumers / GPU utilization / assign a vGPU profile	vmware-privateai (this)
List PAIS served models / knowledge bases	vmware-privateai (this)
Power off / snapshot / clone / migrate the backing vCenter VM	vmware-aiops
Read-only vSphere inventory / alarms / host health	vmware-monitor
GPU-enabled Tanzu Kubernetes clusters / namespaces	vmware-vks
Multi-step GPU workflow with approval + rollback	vmware-pilot

Common Workflows

1. Find an idle GPU and reassign a VM's vGPU profile.

text

vmware-privateai gpu device-list --vendor NVIDIA     # find GPUs; vm_count 0 = idle
vmware-privateai gpu consumer-list                   # who holds a vGPU, and which profile
vmware-privateai vgpu profile-list --host esx-07     # profiles that host can hand a VM
vmware-privateai gpu vgpu-assign fin-train-01 grid_a100-4c --dry-run   # preview blast radius
# power the VM off with vmware-aiops, THEN:
vmware-privateai gpu vgpu-assign fin-train-01 grid_a100-4c             # double-confirm + audit

Failure branch: if vgpu-assign (confirm) refuses with "VM is powered on — a vGPU change needs the VM powered off", run vmware-aiops vm_power_off 'fin-train-01' first, then re-run. If it fails with "profile not offered by the VM's host / GPU lacks free framebuffer", run vmware-privateai gpu host-get <that VM's host> to see the valid profiles and free capacity.

2. Triage GPU utilization across the estate.

text

vmware-privateai gpu utilization --top 10            # busiest vGPU VMs first
vmware-privateai gpu host-list --vendor NVIDIA       # which hosts carry the load

Failure branch: a VM showing metrics unavailable (no host driver?) is not an error — the NVIDIA host GPU driver is not exposing counters for it (metrics_available:false). Deep per-SM / per-process / MIG-slice telemetry is not available via vSphere; use NVIDIA DCGM on the host for that.

3. See what Private AI Service is serving.

text

vmware-privateai pais model-list                     # OpenAI-compatible /models
vmware-privateai pais kb-list                         # RAG knowledge bases

Failure branch: HTTP 404 usually means a base-URL mismatch, not a bug — the /api/v1 PAIS path prefix is deployment-specific and unconfirmed (beta). Check pais.endpoint in config.yaml. HTTP 401/403 means the bearer token in VMWARE_PRIVATEAI_PAIS_TOKEN is expired or lacks scope — obtain a fresh token from your Identity Provider, re-export it, and retry.

Usage Mode

• CLI — interactive inventory / triage, scripting, small or local models (lower context cost).
• MCP — agent-driven operations with structured JSON; run vmware-privateai mcp (an installed console script, so no uvx network re-resolve — works through enterprise TLS proxies, 踩坑 #25).

MCP Tools (17 — 16 read, 1 write)

Category	Tools	R/W
GPU inventory	gpu_host_list, gpu_host_get, gpu_device_list, gpu_consumer_list	Read
GPU utilization	gpu_utilization	Read
GPU readiness	gpu_host_readiness	Read
Profile catalog	vgpu_profile_list, directpath_profile_list	Read
Profile validation	vgpu_profile_validate	Read
Private AI Service	pais_model_list, pais_model_catalog, pais_knowledge_base_list, pais_data_source_list	Read
PAIS monitoring	pais_monitoring_summary	Read
Sizing & air-gap	pais_sizing_advise, pais_bundle_verify	Read
vGPU assignment	vgpu_assign	Write

INFERRED PAIS paths: pais_model_catalog and pais_data_source_list hit PAIS control-plane paths that are unconfirmed against a live OpenAPI (踩坑 #36) — a 404 returns a base-URL teaching message, not a bug. pais_sizing_advise and pais_bundle_verify need no connection (pure computation / local file parse). gpu_host_readiness reports what the vSphere API exposes and says so where it cannot (NVIDIA driver / MFT VIB / MIG need nvidia-smi on the host).

List envelope: every *_list tool returns {items, returned, limit, offset, total, truncated, hint} — read rows from items and check truncated before concluding a listing is complete; empty items with truncated:false means checked-and-none, not a failure. Lists paginate at limit=50; filter with the tool's name/vendor/host/profile/vm arguments rather than paging the whole estate.

Write safety (normative): vgpu_assign with confirm=false (the default) returns blast_radius and changes nothing — VM name and id, current and target profile, device_change (edit the existing vGPU device or add one), other passthrough devices left untouched, power state, blockers, unmeasured. The acting response carries it too. Show it to the user and pass confirm=true only after they agree — the user asking earlier is not agreement, they have not seen it. confirm=true is refused for a powered-on or suspended VM, a name shared by several VMs, and an unreadable power state or device list. It never powers the VM off itself, waits for the real ReconfigVM task outcome (never a premature "ok"), and audits every applied change to ~/.vmware/audit.db.

CLI Quick Reference

bash

vmware-privateai gpu host-list [--name N] [--vendor V]       # hosts with a GPU
vmware-privateai gpu host-get <host>                          # full per-GPU detail
vmware-privateai gpu device-list [--host H] [--vendor V]     # physical GPUs (vm_count 0 = idle)
vmware-privateai gpu consumer-list [--profile P] [--vm V]    # VMs holding a vGPU + profile
vmware-privateai gpu utilization [--vm V] [--top N]          # real-time GPU %, mem %, temp
vmware-privateai gpu vgpu-assign <vm> <profile> [--dry-run]  # WRITE — VM must be off; double-confirm
vmware-privateai gpu readiness [--host H]                   # per-host vGPU/PAIS readiness verdict
vmware-privateai vgpu profile-list [--host H] [--model M]    # vGPU profile catalog
vmware-privateai vgpu directpath-list [--vendor V]           # DirectPath profiles (vSphere 9.0+)
vmware-privateai vgpu validate <vm> <profile>               # pre-flight a vGPU profile change (read-only)
vmware-privateai pais model-list [--name N]                  # PAIS served models
vmware-privateai pais model-catalog [--name N]               # PAIS deployable/approved model catalog
vmware-privateai pais kb-list [--name N]                     # PAIS knowledge bases
vmware-privateai pais data-source-list [--name N]            # PAIS RAG data sources
vmware-privateai pais monitoring-summary [--top N]           # fleet GPU rollup (util/mem/temp, hot/idle)
vmware-privateai pais sizing --model llama-70b               # LLM GPU/storage sizing (no connection)
vmware-privateai pais bundle-verify <pais.yml>              # local air-gap image inspector (no network)

Full list: references/cli-reference.md. Per-tool response-token estimates: references/capabilities.md.

Troubleshooting

• Password not found for target '<t>'. Set environment variable VMWARE_PRIVATEAI_<T>_PASSWORD — add that line to ~/.vmware-privateai/.env and chmod 600 it, or export it (from a secret manager). The <T> is the target name upper-cased with -→_.
• TLS verification failed for target '<t>' — for a self-signed lab set verify_ssl: false for that target in config.yaml; otherwise install the vCenter CA on this host.
• gpu host-list returns nothing on a cluster you know has GPUs — only shared / direct / sharedDirect graphics types count as compute GPUs (the plain host framebuffer is excluded). If real 9.x hardware surfaces a GPU under an unexpected type, that is a beta known-limitation — file an issue with the raw gpu host-get output so the projection can be widened.
• gpu utilization shows a VM with metrics unavailable — the NVIDIA host GPU driver is not exposing counters for it (not an error). Note the gpu.* perf counters may report at host level on some builds — verify the entity type on real hardware (beta caveat).
• directpath-list errors with "needs vCenter 9.0+" — DirectPathProfileManager is new in vSphere 9.0; on 8.x use vgpu profile-list instead (the error routes you there, not an empty list).
• PAIS 404 / non-JSON response — the /api/v1 prefix is deployment-specific and unconfirmed; check pais.endpoint (a proxy or login page returns non-JSON). PAIS 401/403 → refresh the bearer token in VMWARE_PRIVATEAI_PAIS_TOKEN.

Audit & Safety

1. Source Code — https://github.com/vmware-skills/VMware-PrivateAI (MIT).
2. Config File Contents — config.yaml holds target host/username/port and the pais.endpoint only; passwords and the PAIS bearer token live in ~/.vmware-privateai/.env (0600, obfuscated to b64: at rest — obfuscation, not encryption).
3. Webhook Data Scope — none. This skill makes no outbound calls except to the configured vCenter/ESXi targets and PAIS endpoint.
4. TLS Verification — on by default; verify_ssl: false is per-target (and pais.verify_ssl) and only for self-signed labs.
5. Prompt Injection Protection — all vSphere-supplied and PAIS-supplied text (device/vendor/VM/ profile names, PAIS model ids, knowledge-base descriptions) passes through vmware_policy.sanitize() (truncation ≤500 chars + C0/C1 control-char stripping); a KB description is the highest-value injection surface here.
6. Least Privilege — read-vs-write authorization is the vCenter role's job: a read-only service account refuses vgpu_assign's ReconfigVM at vCenter, un-bypassably. All writes are recorded in ~/.vmware/audit.db. See references/setup-guide.md.

License

MIT