Qubes

Autonomous AI workflows inside a Qubes-isolated sandbox. AI agents get real capabilities — provisioning qubes, building templates, running pentests, moving files between them — while the operator's actual system stays structurally invisible to the agent. Qubes provides kernel-level isolation; this project provides the capability surface AI agents need, mediated by dom0 wrappers so the trust boundary is enforced, not trusted.

Threat-model-driven implementation: human-designed boundaries, AI-assisted code. Review from Qubes engineers welcome and needed.

FastMCP server that exposes a tag-scoped Qubes Admin API sandbox to AI assistants. An untrusted-AI principal runs inside a dedicated qube (mcp-control) and can manage a subset of qubes carrying the ai-managed tag — without dom0 access, without visibility into untagged qubes, and without the ability to mutate tags.

Stages A through F3 and the Stage I Wave-1 sub-stages (I-0..I-5) are tested and working on Qubes R4.3-era systems — see the Status table below. Stages G–H are designed but deferred until Stage I completes.

Architecture

Every privileged action the AI takes is mediated by dom0. The MCP principal reaches dom0 only through qrexec; dom0 enforces the invariants and acts on the sandbox on its behalf. The AI never touches qubesd directly and never sees outside its tag scope.

  ── dom0  (TRUSTED) ────────────────────────────────────────────────
     qrexec policy:   policy/30-mcp-control.policy
     qmcp.* wrappers: force-tag on create, cross-ref checks, opaque errors
     operator sets the `ai-managed` tag here, by hand (qvm-tags)
          ▲
          │  qrexec only — no dom0 shell; target=@adminvm routes to dom0
          │
  ── mcp-control  (UNTRUSTED — the AI / MCP principal) ───────────────
     cannot reach a dom0 shell · cannot see untagged qubes · cannot set/remove tags
          │
          │  dom0 acts on its behalf, only on tagged qubes ↓
          ▼
  ── qubes tagged `ai-managed`  (THE SANDBOX) ────────────────────────
     ai-vm-1   ai-vm-2   ai-dvm   …
     network egress funnels through one qube — ai-net-router — whose
     upstream only the operator sets in dom0 (Stage C)

  untagged qubes  =  the operator's real system  =  invisible to the AI

Design highlights

• Tag-scoped trust boundary. AI sees and modifies only qubes carrying the ai-managed tag. The qrexec policy hard-denies admin.vm.tag.{Set,Remove} for the MCP source qube; tagging happens only in two places: the operator's hand in dom0 (qvm-tags <vm> add|del ai-managed) and the create-time wrapper qmcp.SpawnAIManagedQube, which force-tags every qube it creates.
• Dom0-mediated wrappers (qmcp.*). State-changing calls route through small Python scripts in /etc/qubes-rpc/ that enforce invariants in dom0 before touching qubesd: forced tagging on creation, cross-reference validation on template/netvm/default_dispvm, opaque error responses.
• Wrapped reads hide existence. qmcp.GetPropertyAIManaged returns the literal string "not found" indistinguishably whether the target qube doesn't exist or simply isn't tagged. The MCP-side helper normalises all qrexec failure modes (policy deny, no-such-VM, transport error) to the same opaque "not found or refused" so the lifecycle path doesn't leak either.
• Multi-stage rollout, reversible at each step. See CLAUDE.md for the full 8-stage design. Each stage has its own install-*.sh, uninstall-*.sh, and test-*.py in deploy/.

Reviewer asks

This is human-designed, AI-assisted code, and review from people who know the Qubes Admin API and qrexec policy (R4.2+) is genuinely wanted. The detailed, numbered questions — existence-oracle robustness at the qrexec layer, @tag: matching on klass=DispVM, single-egress vs. cascade as a Qubes idiom, event-stream payload minimisation, cap-as-contract disk budgeting, security-tag inheritance on clone_vm / CreateDisposable (a created qube must be stripped to its umbrella, not assumed clean), and more — are written up in OPEN_QUESTIONS.md.

Where this has been discussed:

• qubes-devel design review — five Admin API / qrexec questions, answered point by point by the Qubes project lead: https://groups.google.com/g/qubes-devel/c/4NuSqL64DVE
• Qubes forum thread — original write-up and discussion: https://forum.qubes-os.org/t/41387
• Background — the threat-model case for moving MCP trust boundaries below the protocol: https://alexschose.com/writing/mcp-trust-boundaries-belong-below-the-protocol.html

Status

Stages A through F3 land the binary trust boundary: a qube tagged ai-managed is visible and acted on through the qmcp.* wrappers; an untagged qube is invisible. The F band closes that surface with disk-budget visibility (F3).

Stage I (graduated authority) is the current work line. It adds graduated authority within ai-managed — resource tiers, an action gate (per-call consent for destructive ops), per-trust-class source qubes, a sign-only secrets vault, and persona presets — so a hallucinating or prompt-injected agent cannot destroy real data inside the boundary just because it has a qrexec channel. Stage I lands as sub-stages I-0..I-11 in three waves; I-0 (cap-as- gate), I-1 (read-surface scope redaction), I-2 (dom0 audit log), I-3 (the tier taxonomy + resolution helper, landed behaviour-neutral), I-4 (tiers on the policy-scoped surfaces), and I-5 (tiers on the wrapper

• exec surfaces, with the least-privilege flip available) are done — all listed below. Wave 1 (I-0..I-5) is complete, behaviour-neutral until the operator tiers the fleet and runs the flip; Wave 2 (I-6..I-8, the action gate) is next. Stage G0 (gateway input boundary) was pulled ahead of Wave 2 — a 2026-07-24 architecture review found reachable boundary breaks in the shipped tree, so the tier-independent hardening that closes them shipped now (see the G0 row). The rest of Stage G (mcp-control host hardening, G1/G2) and Stage H remain deferred until Stage I completes — both depend on a non-binary trust model (G1's lockdown is per-tier; H's remote reach needs Stage I's dom0 gate-lift).

Stage	Capability	State
A	Tag-scoped lifecycle + spawn + wrapped property read/write + existence hiding	tested
B	Root command execution + inter-qube file transfer inside ai-managed qubes	tested
C	Single-egress network sandbox (ai-net-router chokepoint, operator-chosen upstream, tag-scoped firewall control)	tested
D	Clone (qmcp.CloneAIManagedQube) + DispVMTemplate/DispVM klass support in qmcp.SpawnAIManagedQube + dom0 lifecycle wrapper (qmcp.LifecycleAIManaged) covering klass=DispVM uniformly	tested
E1	Device attach/detach (qmcp.AttachDeviceAIManaged / qmcp.DetachDeviceAIManaged) between ai-managed qubes, plus tag-scoped block/usb/mic enumeration	tested
E2	Ephemeral DispVMs via qmcp.SpawnDisposableAIManaged (auto-cleanup on shutdown) + qubes_run_disposable one-shot	tested
F1	Wrapped feature.Set (qmcp.SetFeatureAIManaged) — internal denied (operator-only), opaque cross-ref for audiovm/guivm, echoes post-set value; direct feature.Set stays denied	tested
F2	Filtered event stream (qmcp.AIManagedEvents) — bounded-window batch (duration clamped [1, 120]s) of admin events whose subject is ai-managed; minimal {event, subject, subject_klass, ts} payload with whitelisted tag kwarg for tag-add/delete; ships with the opaque-cross-ref backport on SetPropertyAIManaged + SpawnAIManagedQube (closes reviewer ask #8)	tested
F3	AI-scoped disk-budget visibility (qmcp.GetPoolStats) — sum of the persistent footprint of every ai-managed qube (each private, plus root for persistent-root klasses; COW root + ephemeral volatile excluded) + operator cap from /etc/qmcp/pool-cap (re-read per call); returns {used, cap, headroom}; pool topology and operator-side volumes intentionally absent. Cap is a contract operator → AI, not a sensor. (Accounting corrected 2026-06-12 — was every volume's provisioned size, which over-stated real usage ~8×.)	tested
I-0	F3 cap promoted from advisory signal to a hard gate on every create path (qmcp.SpawnAIManagedQube / qmcp.CloneAIManagedQube / qmcp.SpawnDisposableAIManaged). Refuses with opaque "pool cap exceeded" before the Admin API call; measurement is byte-identical to F3 (shared qmcp_budget.py) so AI's (used, cap, headroom) predicts the gate. A per-qube ceiling /etc/qmcp/private-cap bounds any one qube's persistent private (a spawn may request a bigger private_size up to it). Because a volume can't exceed its size, Σ persistent ≤ cap is a hard ceiling on real usage. Cross-ref refusal still wins; caps fail closed. No new RPC, no policy change. First sub-stage of Stage I.	tested
I-1	Read-surface name-leak fix (finding F-3): every VM-valued property read (netvm/template/default_dispvm/guivm/audiovm/management_dispvm) and the list template field is routed through a shared dom0 redactor (qmcp_scope.py) — a referenced qube's name survives only if it is itself ai-managed, else collapses to the opaque <out-of-scope> sentinel; tags reads are filtered to the qmcp vocabulary. The read-path sibling of the F2 write-path cross-ref opacity. Patches the two read wrappers; no policy change, no new RPC.	tested
I-2	Hash-chained, AI-unreachable dom0 audit log of every state-changing qmcp.* call. A shared dom0 helper (qmcp_audit.py) appends one JSON line per call to /var/log/qmcp-audit.log (root:qubes 0660, O_APPEND + flock); each line carries the sha256 of the previous, so any edit/delete/reorder breaks the chain (verify() + a python3 qmcp_audit.py verify CLI re-check it). The 8 state-changing wrappers route their single emit() funnel through audit() and log a whitelisted summary (qube names / property + feature keys / action) — never a property/feature value. Best-effort (never blocks an op); AI-unreachable by construction (no service reads the log; no policy line exposes it). Foundational before the tier model. No new RPC, no policy change.	tested
I-3	Tier taxonomy + dom0 tier-resolution helper — the keystone of the resource axis. Graduates the binary boundary into a cumulative ladder within ai-managed: ai-managed (read floor) < ai-exec (+commands) < ai-net (+firewall write) < ai-full (+lifecycle/property/clone/spawn/feature/attach/detach); ai-dump is an orthogonal copy-IN-only sink. A shared dom0 helper (qmcp_tier.py, sibling-loaded like qmcp_budget/qmcp_scope/qmcp_audit) exposes effective_capabilities(vm) → a frozenset of capability tokens, so the wrappers ask CAP_FULL in caps and stay decoupled from the taxonomy. Behaviour-neutral: ships inert (no wrapper sources it until I-5) in compat mode (untiered ai-managed = full = today's boundary). AI can neither mutate tags (keystone) nor read the tier tags (a tags read stays ["ai-managed"] — the authority topology is not an oracle). Two-phase migration: enforce in I-4/I-5, then flip /etc/qmcp/tier-default to ro for least privilege. No new RPC, no policy change.	tested
I-4	First enforcement step of the resource axis — a single-file policy diff graduating the directly-@tag:-scoped surfaces. firewall.Get + device-list stay at the ai-managed ro-floor; firewall.{Set,Reload} move to @tag:ai-net + @tag:ai-full; ai-dump gets a dedicated copy-IN-only qubes.Filecopy * @tag:ai-managed @tag:ai-dump allow (the Biba write-only sink — a pure ai-dump qube is push-only and invisible to reads/list/exec because it lacks the umbrella; the write-only property rests on the operator invariant that an ai-dump qube is never also ai-managed, which the installer checks and I-5 enforces). The policy layer matches tags literally and cannot call qmcp_tier, so firewall-write ships with a @tag:ai-managed compat backstop (keeps untiered qubes writable through migration → A–F3 stays green and the live egress qube keeps firewall control on deploy; behaviour-neutral on firewall in compat — only the ai-dump valve is new live behaviour). The flip (end of I-5) deletes the backstop and writes ro to /etc/qmcp/tier-default in one change. Policy-only; no new RPC, no new qube, no wrapper change. Proven offline (100-check policy simulation, compat + post-flip), a per-tier hardware slot, and an AI-side transparency test.	tested
I-5	Second enforcement step — tiers on the @adminvm wrapper surfaces (dom0 code) + the exec surfaces (policy), then the least-privilege flip. Lifecycle/SetProperty/SetFeature require ai-full on the target, Clone on the source, Spawn on the template, SpawnDisposable on the DVMT, Attach/Detach on both endpoints — via the sibling-loaded qmcp_tier helper, fail-closed (a missing/broken resolver denies, never allows). RunInAIManaged/CopyToAIManaged graduate in policy to @tag:ai-exec/ai-net/ai-full + a @tag:ai-managed compat backstop (mirrors I-4 firewall). Every create path strips any tier tag the platform propagates — clone_vm copies the source's tags, CreateDisposable inherits the DVMT's — so a created qube is always untiered (umbrella only); without the strip, AI could clone an ai-full qube into another and self-escalate past the flip. Behaviour-neutral in compat (untiered = full). The flip (separate slot, after the operator tiers the fleet) deletes four compat backstops (firewall.Set/Reload + Run/Copy) and writes ro to /etc/qmcp/tier-default in one coupled change. No new RPC, no new qube, no new ring. Proven offline (260 checks: wrapper-gate suite + policy simulator + I-4 regression) and on dom0 hardware (per-tier gate + the create-path strip, read back via qvm-tags in dom0 since tier tags are AI-unreachable).	tested
G0	Gateway input boundary (pulled ahead of Wave 2 after the 2026-07-24 review). Property allowlist — provides_network operator-only (no self-minted egress); qrexec target-name validator (@adminvm/dom0/malformed rejected before any call); device enumeration (attached + available) routed through the dom0 redactor qmcp.ListAttachedDevicesAIManaged that hides out-of-scope backend/consuming-frontend qube names, with direct admin.vm.device.* enumeration denied; qubes.Filecopy re-tiered to ai-exec on both endpoints + explicit deny (no fleet-wide push into ai-ro qubes); mask_error_details + opaque error collapse. Closes four review findings; offline + per-fix hardware slots green.	tested
G1/G2	mcp-control host hardening (sudo lockdown, dedicated MCP user) + Tor hidden service for sshd → mobile CLI reach	designed — deferred until Stage I completes
H	FastMCP HTTP/SSE bound to a second .onion → mobile-app reach	designed — deferred until Stage I completes

See CLAUDE.md for the full design document — trust model, anti-goals, file layout, and operating protocol.

Naming conventions (load-bearing)

The qrexec policy file references two names that must match your system:

• mcp-control — the qube that runs this MCP server. The policy file hard-codes this as the source for every allow rule. If you must use a different name, change every mcp-control token in policy/30-mcp-control.policy and in the install scripts before deploying.
• ai-managed — the qrexec tag that defines the sandbox. Don't rename unless you also update every @tag:ai-managed reference in the policy and every "ai-managed" literal in the qmcp.* scripts.

The Python package directory is qubes_mcp/ inside the repo root. If you pip install -e . inside your venv (recommended), the package resolves natively and the test scripts' fallback sys.path insert is harmless.

Setup

This involves three locations on a Qubes host:

1. The mcp-control qube — runs the MCP server, holds the working tree.
2. Dom0 — receives the qrexec policy and the qmcp.* services.
3. One ai-managed template — receives qmcp.RunInAIManaged and qmcp.CopyToAIManaged in Stage B (the install script handles this).

Step 1 — Create mcp-control and install dependencies

In dom0:

qvm-create --class StandaloneVM --label gray --template debian-13 mcp-control

Then in the new qube:

sudo apt install -y qubes-core-admin-client openssh-server ca-certificates git python3-venv
git clone https://github.com/alex-schose/qubes-mcp.git qubes_mcp
cd qubes_mcp
python3 -m venv --system-site-packages .venv
.venv/bin/pip install -e .

--system-site-packages lets the venv see qubesadmin (provided by the qubes-core-admin-client apt package). pip install -e . installs the qubes_mcp package in editable mode using pyproject.toml; this provides the qubes-mcp-server console entrypoint and lets the tests find the package by name from any working directory.

Step 2 — Deploy Stage A (from dom0)

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-a.sh' > /tmp/install-a.sh
less /tmp/install-a.sh         # review before executing
bash /tmp/install-a.sh mcp-control ~user/qubes_mcp

The two positional arguments are the source qube and the path to the repo inside it. Defaults: mcp-control and /home/user/qubes_mcp. Pass them explicitly if you cloned to a different location.

The script clones debian-13 → ai-debian-13 (if needed), tags it ai-managed, and installs the policy + qmcp scripts.

Step 3 — Verify Stage A (from mcp-control)

cd ~/qubes_mcp
.venv/bin/python deploy/test-stage-a.py

(All test scripts work from any cwd — they self-locate the package.)

Expect five PASS markers: existence-leak hidden; SetProperty cross-ref opaque byte-identical; Spawn template cross-ref opaque byte-identical; policy refusal on untagged; remove confirmation. The opaque-cross-ref assertions land in the Stage A wrappers that install-stage-a.sh ships today (they were backported in the Stage F2 bundle — see reviewer ask #8), so a fresh install passes 5/5. If you're upgrading an older deployment, expect the SetProperty and Spawn cross-ref markers to FAIL until you ship Step 10 (which replaces the older wrappers with the opaque-collapse versions).

Step 4 — (Optional) Deploy Stage B for command exec + file transfer

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-b.sh' > /tmp/install-b.sh
bash /tmp/install-b.sh mcp-control ~user/qubes_mcp

Stage B briefly starts the ai-debian-13 template, installs the two template-side services into /etc/qubes-rpc/, and shuts the template back down to commit changes.

Then from mcp-control:

.venv/bin/python deploy/test-stage-b.py

Four more PASS markers.

Step 5 — (Optional) Deploy Stage C for the single-egress network sandbox

Stage C creates one ai-managed network qube — ai-net-router — that all AI qubes route through by default. The operator chooses ai-net-router's upstream in dom0 (sys-firewall for clearnet, sys-whonix for Tor, a VPN qube, or "" for offline); AI cannot change this. AI can still read and set firewall rules on ai-net-router and on its own qubes.

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-c.sh' > /tmp/install-c.sh
EGRESS_UPSTREAM=sys-firewall bash /tmp/install-c.sh mcp-control ~user/qubes_mcp

Configurable via env vars (with defaults):

• EGRESS_UPSTREAM=sys-firewall — ai-net-router's netvm (any existing qube, or "").
• EGRESS_TEMPLATE=fedora-43-xfce — the AppVM template for ai-net-router.
• EGRESS_LABEL=red — Qubes colour.
• EGRESS_MEMORY=500 — RAM in MiB.

Switch the upstream any time:

qvm-prefs ai-net-router netvm <new-upstream>

Then from mcp-control:

.venv/bin/python deploy/test-stage-c.py

Eight PASS markers — egress visibility, default-netvm application, explicit-null preservation, egress-qube lock, AI-qube netvm retarget, firewall rules round-trip, untagged-target refusal, and former-ai-sys invisibility.

Step 6 — (Optional) Deploy Stage D for cloning + DispVM klass support

Stage D adds three things: qmcp.CloneAIManagedQube (clone an ai-managed qube into a new ai-managed qube), the DispVMTemplate and DispVM klasses in qmcp.SpawnAIManagedQube, and qmcp.LifecycleAIManaged (a dom0 wrapper that replaces the Stage A admin.vm.* tag-scoped lifecycle allow lines because qrexec's @tag: selector doesn't reach klass=DispVM targets — see reviewer ask #6). No new dom0 provisioning — only the policy + RPC scripts change.

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-d.sh' > /tmp/install-d.sh
bash /tmp/install-d.sh mcp-control ~user/qubes_mcp

Then from mcp-control:

.venv/bin/python deploy/test-stage-d.py

Six PASS markers — clone of ai-managed succeeds, clone of untagged refuses opaquely, DispVMTemplate spawn sets template_for_dispvms, DispVM spawn inherits template + ai-managed tag, DispVM from a plain TemplateVM is refused by the template_for_dispvms cross-ref, and end-to-end usability (start ai-dvm + run whoami as root inside via qmcp.RunInAIManaged + clean shutdown — proves the ai-debian-13 → DVMT → DispVM service-inheritance chain).

Step 7 — (Optional) Deploy Stage E1 for device attach between ai-managed qubes

Stage E1 adds two dom0 wrappers (qmcp.AttachDeviceAIManaged, qmcp.DetachDeviceAIManaged) that attach virtual block/USB/mic devices between ai-managed qubes. Both backend and frontend must be ai-managed; the wrapper collapses missing/untagged on either side to opaque "not found". Read-only enumeration (admin.vm.device.{class}.{List, Available}) is tag-scoped at the policy layer — same shape as Stage C firewall reads. No new qube provisioning.

In practice, block is the useful case (e.g. shared scratch volume between two ai-managed AppVMs). USB requires sys-usb to be ai-managed and mic requires the audio backend to be ai-managed — both operator opt-ins. Default install leaves these dormant; the wrappers are ready when the operator chooses to tag those backends.

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-e1.sh' > /tmp/install-e1.sh
bash /tmp/install-e1.sh mcp-control ~user/qubes_mcp

Then from mcp-control:

.venv/bin/python deploy/test-stage-e1.py

Six PASS markers (hard): tag-scoped list on ai-managed backend succeeds; list on untagged refuses opaquely; attach refuses when either endpoint is untagged; same for detach. Plus a SOFT block of informational checks for a real loop-device round-trip (template- dependent — qubes-core-agent's block enumerator may or may not auto-expose /dev/loop* on a given Debian build, so those are reported but not counted toward the pass total).

Step 8 — (Optional) Deploy Stage E2 for ephemeral DispVMs

Stage E2 adds qmcp.SpawnDisposableAIManaged — a dom0 wrapper around admin.vm.CreateDisposable. The DVMT (DispVMTemplate, created in Stage D) must be ai-managed and have template_for_dispvms=True; the auto-named disposable (dispXXXX) is force-tagged before AI sees it; auto_cleanup=True is the Admin API default, so dom0 removes the qube once it halts. admin.vm.CreateDisposable stays denied — the wrapper is the only allowed path.

MCP also ships qubes_run_disposable(template, cmd) — a one-shot that composes spawn → start → run → shutdown without adding any new dom0 surface. The typical "fire a throwaway, get its output, move on" pattern collapses to a single call.

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-e2.sh' > /tmp/install-e2.sh
bash /tmp/install-e2.sh mcp-control ~user/qubes_mcp

Then from mcp-control:

.venv/bin/python deploy/test-stage-e2.py

Five PASS markers: spawn+tag+klass+template+auto_cleanup; start+ whoami=root+shutdown+auto-removed; plain-TemplateVM cross-ref refusal; untagged-DVMT opaque refusal; one-shot end-to-end.

Step 9 — (Optional) Deploy Stage F1 for feature.Set

Stage F1 adds qmcp.SetFeatureAIManaged — a dom0 wrapper around admin.vm.feature.Set on ai-managed qubes. The internal feature is refused (operator-only — AI must not hide a qube from your menus), and the cross-VM keys audiovm/guivm must point at an ai-managed qube (refused opaquely otherwise). Direct admin.vm.feature.Set stays denied — the wrapper is the only path — and no feature-read surface is exposed (the wrapper echoes the post-set value instead). No new dom0 provisioning — only the policy + RPC script change.

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-f1.sh' > /tmp/install-f1.sh
bash /tmp/install-f1.sh mcp-control ~user/qubes_mcp

Then from mcp-control:

.venv/bin/python deploy/test-stage-f1.py

Five PASS markers: round-trip set + value echo + boolean coercion; internal refused; cross-ref to an ai-managed qube accepted; cross-ref to an untagged AND a nonexistent qube both refused with the same opaque message (no existence leak); feature.Set on an untagged qube refused with the opaque "not found".

Step 10 — (Optional) Deploy Stage F2 for filtered event streaming

Stage F2 adds qmcp.AIManagedEvents — a dom0 wrapper that subscribes to admin.Events with full admin authority, filters every event by the ai-managed tag on its subject, and returns the collected batch when the caller-given duration (clamped to [1, 120] seconds) elapses. No persistent dom0 process — one invocation, one window, one JSON response, exit. Direct admin.Events stays denied — the wrapper is the only path. AI catches the immediate consequence of an action by opening the window FIRST (a concurrent tool call) and then acting; the bounded-window model trades inter-call event coverage for a stateless dom0 footprint.

This step also backports the opaque-cross-ref collapse to qmcp.SetPropertyAIManaged and qmcp.SpawnAIManagedQube (closes reviewer ask #8 — the same existence-oracle gap F1 closed on SetFeatureAIManaged, finally aligned across all write/spawn surfaces).

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-f2.sh' > /tmp/install-f2.sh
bash /tmp/install-f2.sh mcp-control ~user/qubes_mcp

Then from mcp-control:

.venv/bin/python deploy/test-stage-a.py    # 5 PASS — re-verifies the opaque-collapse backport
.venv/bin/python deploy/test-stage-f1.py   # 5 PASS — unchanged
.venv/bin/python deploy/test-stage-f2.py   # 5 PASS — new events surface

Stage F2's five PASS markers: ai-managed domain-start IS surfaced inside the window; no event with a non-ai-managed subject leaks through; qube filter restricts the batch to the requested qube; qube filter is opaque on missing/untagged (byte-identical "not found"); events filter restricts the batch to event names matching exactly OR as a "<entry>:" prefix.

Step 11 — (Optional) Deploy Stage F3 for AI disk-budget visibility

Stage F3 adds qmcp.GetPoolStats — a dom0 wrapper that returns the total persistent provisioned footprint across every ai-managed qube (each private, plus root for persistent-root klasses; COW root and ephemeral volatile excluded — corrected 2026-06-12, was every volume), plus an operator-set ceiling read from /etc/qmcp/pool-cap. AI gets {used, cap, headroom} and can self-throttle spawn loops before the cap is hit. Pool names, free-space, total-pool-size, and any operator-side volume are intentionally absent — the wrapper returns only AI's own footprint and the budget the operator gave it.

The cap is operator-defined, not operator-observed (a "free-space" shape would have been a streaming operator-side oracle — free bytes drop whenever the operator does anything). The cap file is a single integer (bytes); the install script seeds it with 50 GiB if absent, and the wrapper re-reads it on every call so operator edits take effect immediately with no daemon restart. Direct admin.pool.* and admin.vm.volume.{List,Info} stay denied — the wrapper bypasses those over the local dom0 socket. No new dom0 provisioning beyond the wrapper + policy + cap file.

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-f3.sh' > /tmp/install-f3.sh
bash /tmp/install-f3.sh mcp-control ~user/qubes_mcp

To change the budget any time (no redeploy needed):

sudo sh -c 'echo 107374182400 > /etc/qmcp/pool-cap'   # 100 GiB

Then from mcp-control:

.venv/bin/python deploy/test-stage-f3.py

Four PASS markers: response shape + arithmetic invariant (used + headroom == cap when within cap); untagged operator volumes excluded (sanity bound); spawn-delta positive + remove returns to baseline; payload ignored (empty kwargs whitelist). Plus a SOFT manual block confirming cap-file edits take effect on the next call without a policy-daemon restart.

Step 12 — (Optional) Deploy Stage I-0 to enforce the F3 pool cap

Stage I-0 promotes the F3 pool cap from an advisory signal that AI is expected to self-throttle on into a hard gate that runs in every create wrapper before the Admin API call. Without this, a hallucinating or prompt-injected agent can ignore F3's (used, cap, headroom) and spawn past the budget (the F-1 finding that motivated this sub-stage). With it, every qmcp.SpawnAIManagedQube, qmcp.CloneAIManagedQube, and qmcp.SpawnDisposableAIManaged call computes projected = current_ai_managed_used + estimate_from(new_qube) and refuses with the opaque "pool cap exceeded" if projected > cap. (Accounting corrected 2026-06-12 — matching the I-0 row in the Status table above: used meters the persistent footprint (each private, plus root only for persistent-root klasses), the estimate is the new qube's private, and a per-qube /etc/qmcp/private-cap bounds any single qube. The form that shipped first summed every volume's provisioned size, ~8× over-counting.)

Measurement is byte-identical to F3's qmcp.GetPoolStats, so AI's view of (used, cap, headroom) predicts the gate's behaviour exactly — there's no new oracle. The cross-ref refusal still fires first, so an untagged template surfaces the same opaque cross-ref message before the gate runs. Cap-missing/malformed/negative fail closed with F3's existing "pool cap not configured" (F3's install seeds the cap, so the unconfigured state is a deliberate operator action). The enforcement logic lives in a shared dom0 helper (/etc/qubes-rpc/qmcp_budget.py) sibling-loaded by each wrapper.

I-0 does not add a new RPC service, does not change the qrexec policy, and does not restart the policy daemon. qmcp.GetPoolStats stays read-only — enforcement lives in the writes, the read is the signal.

Stage F3 is a prerequisite (it seeds /etc/qmcp/pool-cap).

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-I-0.sh' > /tmp/install-I-0.sh
bash /tmp/install-I-0.sh mcp-control ~user/qubes_mcp

Then from mcp-control:

.venv/bin/python deploy/test-stage-I-0.py

Four probes (Spawn / Clone / SpawnDisposable + GetPoolStats shape). Each probe always attempts its create surface and classifies the response across three valid outcomes:

• ok=True → wrapper proceeded under headroom (HARD).
• "pool cap exceeded" → gate fired under cap pressure (SOFT S1).
• "pool cap not configured" → gate fired fail-closed (SOFT S2).

Any other response is a FAIL. The same test therefore PASSes under every cap state; reading the response JSON above each probe tells you which gate path actually fired.

Two SOFT operator-driven cap manipulations exercise S1 and S2:

1. Lower the cap below the current used (in dom0: sudo sh -c 'echo <NEW_BYTES> > /etc/qmcp/pool-cap'), re-run the test, and the response lines now carry "error": "pool cap exceeded" across all three create surfaces.
2. Remove the cap file (sudo rm /etc/qmcp/pool-cap), re-run, and the response lines now carry "error": "pool cap not configured".

Restore the original cap value after testing.

Step 13 — (Optional) Deploy Stage I-1 to close the read-surface name leak

Stage I-1 closes finding F-3. The wrapped reads were opaque on a qube's existence (a missing or untagged target returns the uniform "not found") but not on a property value that referenced another qube: qmcp.GetPropertyAIManaged serialised any VM-valued property (netvm, template, default_dispvm, guivm, audiovm, management_dispvm) to the referent's raw name, and qmcp.ListAIManagedQubes did the same for its template field — so a single read of an ai-managed qube could enumerate out-of-scope operator qube names.

With I-1 both wrappers route every VM-valued result through a shared dom0 redactor (/etc/qubes-rpc/qmcp_scope.py): a referenced qube's name is emitted only if that qube is itself ai-managed, otherwise it collapses to the opaque <out-of-scope> sentinel. The tags read is filtered to the qmcp vocabulary (it was previously hidden only by the accidental non-serialisability of the Tags object). Labels and scalars pass through unchanged, and existence-hiding on the lookup channel is unchanged. This is the read-path sibling of the Stage F2 write-path cross-ref opacity, and it is fail-closed: a read refuses if the redactor can't load.

I-1 does not add a new RPC service, change the qrexec policy, or restart the policy daemon.

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-I-1.sh' > /tmp/install-I-1.sh
bash /tmp/install-I-1.sh mcp-control ~user/qubes_mcp/public

Then verify from mcp-control:

.venv/bin/python deploy/test-stage-I-1.py     # 5 PASS

deploy/uninstall-stage-I-1.sh reverts (restore the pre-I-1 wrappers, then remove the helper).

Step 14 — (Optional) Deploy Stage I-2 for the dom0 audit log

Stage I-2 adds a tamper-evident, AI-unreachable record of every state-changing qmcp.* call. A shared dom0 helper (/etc/qubes-rpc/qmcp_audit.py) appends one JSON line per call to /var/log/qmcp-audit.log (root:qubes 0660, O_APPEND + flock); each line carries the sha256 of the previous line, so any deletion or edit breaks the chain. The 8 state-changing wrappers (Spawn / Clone / SpawnDisposable / SetProperty / SetFeature / Lifecycle / Attach / Detach) each route their single response funnel through audit(), so every call leaves exactly one chained line, and log only a whitelisted summary (qube names / property + feature keys / action) — never a property or feature value.

The log is owned root:qubes 0660: dom0 qrexec services run as a non-root user that is in the qubes group (it must be, to reach qubesd), so group-write is what lets the wrappers append — a root:0600 log would be silently unwritable by them. The installer sets this ownership; the wrappers only append.

Logging is best-effort: a failure never blocks or alters an operation. The log is AI-unreachable by construction — no qmcp.* service reads or writes an arbitrary dom0 path and no policy line exposes it, so an ai-managed qube can neither read past entries nor forge new ones (AI has no dom0 file access at all; the qubes-group write applies only to dom0-local processes, never to AI). I-2 does not add a new RPC service, change the qrexec policy, or restart the policy daemon.

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-I-2.sh' > /tmp/install-I-2.sh
bash /tmp/install-I-2.sh mcp-control ~user/qubes_mcp/public

Inspect and verify the trail in dom0:

sudo tail -n 5 /var/log/qmcp-audit.log
sudo python3 /etc/qubes-rpc/qmcp_audit.py verify     # walks the chain

Then check transparency from mcp-control (the log is unreadable from here by design — chain integrity is verified in dom0, above):

.venv/bin/python deploy/test-stage-I-2.py     # 3 PASS

deploy/uninstall-stage-I-2.sh removes the helper (safe — the hook is best-effort, so the wrappers keep working without it); /tmp/run.sh revert restores the pre-I-2 wrapper source too.

Step 15 — (Optional) Deploy Stage I-4 for tiered policy surfaces

Stage I-4 is the first enforcement step of the resource axis — a single-file policy diff (no new RPC script, no new qube, no wrapper change). It graduates the directly-@tag:-scoped surfaces:

• firewall.Get and device.*.{List,Available} stay at the ai-managed ro-floor (unchanged).
• firewall.{Set,Reload} move to @tag:ai-net + @tag:ai-full.
• ai-dump gets a dedicated qubes.Filecopy * @tag:ai-managed @tag:ai-dump allow — a copy-IN-only sink. A pure ai-dump qube is not tagged ai-managed, so every read / exec / firewall / device surface misses it by construction: AI can push data to it but never read it back. Operator invariant: an ai-dump qube must never also be ai-managed — a hybrid is fully readable (the inter-copy line matches it as a source), defeating the valve. AI cannot create one (it cannot mutate tags), and the installer warns on any hybrid; I-5 machine-refuses it at fleet-tiering.

The policy layer matches @tag: selectors literally and cannot call the qmcp_tier helper, so it cannot honour the helper's "untiered = ai-full (compat)" default. I-4 therefore ships firewall-write with a @tag:ai-managed compat backstop that keeps untiered umbrella qubes writable through migration — so the A–F3 regression stays green and the live egress qube keeps firewall control the moment you deploy. While the backstop is present the firewall-write surface is behaviour-neutral; the one new live capability is the ai-dump valve. The flip (end of Stage I-5) deletes the two backstop lines and writes ro to /etc/qmcp/tier-default in the same change, so the policy surface and the wrapper surface drop to least-privilege together. This step does not require the I-3 helper to be installed (the policy layer never sources it).

From dom0 (the installer validates the policy before replacing the live file — a malformed policy can break all of qrexec):

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-I-4.sh' > /tmp/install-I-4.sh
bash /tmp/install-I-4.sh mcp-control ~user/qubes_mcp/public

Then verify from mcp-control:

.venv/bin/python deploy/test-stage-I-4.py     # 4 PASS — compat invariance + oracle hygiene
.venv/bin/python deploy/test-stage-c.py       # firewall regression: unchanged

The per-tier behaviour (ro/exec denied firewall-write after the flip; net/full allowed) is proven on dom0 hardware by the operator's slot with operator-tagged fixtures, and exhaustively offline by a policy simulator that parses the real file and checks the full (surface × tier) matrix for both compat and post-flip. deploy/uninstall-stage-I-4.sh reverts the policy (or /tmp/run.sh revert restores the pre-I-4 file byte-exact).

Step 16 — (Optional) Deploy Stage I-5 for tiered wrapper + exec surfaces

Stage I-5 is the second enforcement step — it tiers the @adminvm wrapper surfaces (in dom0 code) and the exec surfaces (in policy), completing the resource axis (Wave 1).

• The eight state-changing wrappers (Lifecycle / SetProperty / Clone / Spawn / SetFeature / Attach / Detach / SpawnDisposable) now require ai-full via the sibling-loaded qmcp_tier helper — Lifecycle/ SetProperty/SetFeature gate the target, Clone the source, Spawn the template, SpawnDisposable the DVMT, Attach/Detach both endpoints. The gate is fail-closed: if the resolver can't load, the call is refused (opaque "not found"), never allowed (unlike the best-effort audit hook).
• RunInAIManaged / CopyToAIManaged graduate in the policy to @tag:ai-exec / ai-net / ai-full plus a @tag:ai-managed compat backstop — the same Option-A pattern Stage I-4 used for firewall write.
• Every create path strips any tier tag inherited from its source: qubesadmin.clone_vm copies all of the source's tags (except created-by-*) and admin.vm.CreateDisposable inherits the DVMT's, so without the strip a clone/disposable of an ai-full qube would emerge ai-full — letting AI self-escalate past the flip. The wrappers remove every non-umbrella tier tag on create, verify, and roll back on failure, so a created qube is always untiered.

In compat (the default — /etc/qmcp/tier-default absent → untiered = ai-full) all of this is behaviour-neutral: every A–F3 operation still works. Enforcement bites only once the operator tiers the fleet and runs the flip (a separate step): delete the four compat backstops (firewall.Set/Reload + RunInAIManaged/CopyToAIManaged) and write ro to /etc/qmcp/tier-default in one coupled change, so the policy and wrapper surfaces drop to least-privilege together.

qmcp_tier.py (from Stage I-3) must already be in dom0. The installer verifies it, refuses to install if any qube carries both ai-managed and ai-dump (the hybrid the I-4 valve warns about — I-5 enforces the disjointness), and validates the policy before replacing the live file.

From dom0:

qvm-run --pass-io mcp-control 'cat ~/qubes_mcp/deploy/install-stage-I-5.sh' > /tmp/install-I-5.sh
bash /tmp/install-I-5.sh mcp-control ~user/qubes_mcp/public

Then verify from mcp-control:

.venv/bin/python deploy/test-stage-I-5.py     # compat invariance + opaque tier refusals
.venv/bin/python deploy/test-stage-a.py        # A–F3 regression: unchanged in compat

The per-tier gate (an ai-exec qube refused an ai-full op), the behaviour-neutral compat path, and the create-path strip (a clone of an ai-full source comes back untiered) are proven on dom0 hardware by the operator's slot — the strip is read back via qvm-tags in dom0 because tier tags are deliberately invisible to AI. deploy/uninstall-stage-I-5.sh reverts (or /tmp/run.sh revert restores the pre-I-5 wrappers + policy byte-exact).

Step 17 — Connect a client

From your workstation, configure an MCP client to invoke the server via SSH + stdio. Example for Claude Code (~/.claude.json):

{
  "mcpServers": {
    "qubes": {
      "command": "ssh",
      "args": [
        "-T",
        "user@<mcp-control-host>",
        "/home/user/qubes_mcp/.venv/bin/python",
        "-m",
        "qubes_mcp"
      ]
    }
  }
}

Replace <mcp-control-host> with whatever address reaches your mcp-control qube — typically an isolated overlay network (tailnet, Headscale, WireGuard).

Quick tour

qubes_mcp/                          # repo root
├── CLAUDE.md                       # source-of-truth design doc
├── README.md                       # this file
├── LICENSE                         # MIT
├── pyproject.toml                  # package metadata; `pip install -e .` works
├── qubes_mcp/                      # the Python package
│   ├── server.py                   # FastMCP, Ring enum, ring_tool decorator, spend_gate
│   ├── __main__.py                 # `python -m qubes_mcp` entrypoint
│   └── tools/                      # one file per MCP tool
├── policy/30-mcp-control.policy    # qrexec policy → /etc/qubes/policy.d/ in dom0
├── dom0-rpc/                       # qmcp.* scripts → /etc/qubes-rpc/ in dom0
├── template-rpc/                   # qmcp.* scripts → /etc/qubes-rpc/ inside ai-managed templates
└── deploy/                         # install/uninstall/test for each stage

License

MIT — see LICENSE.

Caveat

This is operator-grade infrastructure for a specific use case (sandboxed AI agents managing Qubes-isolated workloads). It is not a hardened product. The threat model treats the MCP source qube (mcp-control) as itself the trust boundary, and the dom0/policy layer is what enforces it: the qmcp.* wrappers and qrexec policy are built so a compromised mcp-control cannot read, enumerate, mutate, or act on qubes outside its ai-managed tag scope, cannot mint its own network egress, and cannot escalate the authority the operator granted. The gateway-input boundary breaks a 2026-07-24 architecture review surfaced — an unrestricted property write (self-minted egress), device-enumeration oracles reaching dom0, out-of-scope qube names leaking through reads and device lists, and inter-qube file-copy over-reach — are closed in Stage G0. Within its granted scope the AI can do anything. Two honest limits remain: a few pre-existing failure-path error messages can still surface a referenced qube name (being collapsed to opaque refusals), and hardening mcp-control itself (sudo lockdown, dedicated MCP user) is deferred Stage G1/G2 work. Stage I (graduated authority — current work line) tiers authority below the umbrella tag so a compromised or hallucinating agent need not hold full authority on every qube it can see. Run on your own infrastructure; report bugs in issues.