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: v1.0.0 (beta). Skill #15 of the family; independent 1.x version line. 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
Profile catalog	vGPU profile list, DirectPath profile list	2	2 R
vGPU assignment	set a VM's vGPU profile (VM must be powered off)	1	1 W
Private AI Service	served-model list, knowledge-base list	2	2 R

10 MCP tools (9 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.

Quick Install

bash

uv tool install vmware-privateai
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 (10 — 9 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
Profile catalog	vgpu_profile_list, directpath_profile_list	Read
Private AI Service	pais_model_list, pais_knowledge_base_list	Read
vGPU assignment	vgpu_assign	Write

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) previews only — current profile, target profile, power state, and that a power-off is required — without acting. confirm=true applies it, but refuses a powered-on VM with a teaching error. 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 vgpu profile-list [--host H] [--model M]    # vGPU profile catalog
vmware-privateai vgpu directpath-list [--vendor V]           # DirectPath profiles (vSphere 9.0+)
vmware-privateai pais model-list [--name N]                  # PAIS served models
vmware-privateai pais kb-list [--name N]                     # PAIS knowledge bases

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