Pose Lab

Measured spatial answers for posing first-person arms and a rifle in Blender, over MCP.

Models are weak at judging 3D space from pictures: which side of a rifle faces the eye, whether a finger sits inside the receiver, whether any turn of the gun can ever show its ejection port. Pose Lab gives a model numbers instead. It reports positions in named frames and how deep anything clips. It measures how squarely a surface faces the eye and what the eye can see. Its solver searches rifle moves against goals and reports which goals no move can meet. For animation, it scans a clip frame by frame against the same checks and mends what fails.

I built it while hand-making chamber checks for my first-person shooter. One question took me several full Blender runs: can turning the rifle show its ejection port to the eye? With Pose Lab it is one solve call. On my game's AK rig, turning alone met the goal in 0 of 60 samples. That is a fact of the geometry: the eye looks along the barrel. Turning and moving the rifle met each goal on its own, but no sample of 400 met all four goals together. So that check needs a new hand pose, not only a new rifle position. On the built-in sample rig, turning alone also met the port goal in 0 of 60 samples, and turning and moving met every goal in 9 s.

What it gives a model

Frames and signs

Every position goes in and comes out in a named frame, so no one has to guess axes:

• gun: the gun bone as it stands, Unreal-style axes, cm: +X the gun's left, +Y along the barrel, +Z up (the default)
• arms: the arms' space, Unreal-style axes, cm
• view: from the eye, cm: +X right, +Y forward, +Z up

Turns use the player's words: roll + turns the gun's right side up, swing + takes the muzzle left, pitch + the muzzle up. Moves (right, forward, up) are in the view.

A hand round its grip touches the rifle on the idle pose already (a finger on the trigger, fingers round the handguard). Call clearance at pose_idle for that baseline, and leave those segments out with ignore wildcards. On the built-in sample the left thumb sits 2.7 cm inside the handguard at idle. clearance measures to the rifle's surface (inside or out by ray parity), so it sees a body part inside a flat face between the mesh's corner points.

Arm rules (anatomy)

A pose can clear the rifle and still be one no human arm can take. anatomy checks each arm against these limits:

The wrist and elbow ranges are the AAOS normal values, from the AAOS 1965 table as reprinted in Greene and Heckman 1994. Other tables differ, by 10 to 25 degrees for the fingers and thumb. The 30 degree wrist line, the 5 degree elbow minimum and the elbow under the shoulder are working rules for this game's look of a hand on a gun, not joint limits. The wrist rule is stricter than daily tasks: Ryu 1991 found daily tasks use up to 60 degrees of extension and 40 of ulnar deviation. The finger limits allow 10 more flexion than AAOS at the knuckle and the middle joint; docs/ANATOMY.md says why the defaults stay that way. It gives each joint's standard and functional range, the value checked, and the sources (AAOS; Eaton; Morrey 1981; Palmer 1985; Ryu 1991; Hume 1990; Bain 2015; Soucie 2011). arm_ranges returns the same data to a model.

The anatomy reply lists, for each arm, the elbow's height under the shoulder, the elbow's bend, the wrist's bend split into flexion and radial deviation, the wrist's twist, each finger joint's curl and twist, and bad: every rule the pose breaks. Each rule reads the value as reported: angles to the degree, the elbow's height to 0.1 cm. A rig's limits, finger_limits and thumb_limits entries in rigs.json override any value. solve takes {"type": "anatomy"} as a goal.

move_gun, reach and fix_clip place hands with a turn. They move the hand's twist into the forearm, so the wrist joint only bends: a 60 degree rifle roll with the hands kept reads no wrist twist.

Fix a broken rule by moving the rifle, the grip or the elbow's pole. Do not bend a joint further.

The sample rig's idle grip breaks the wrist rule: the left wrist bends 44 degrees off the forearm and the right 58. fix_clip with an anatomy check brings the left to 29. It leaves the right at 58: every turn that mends it puts the rifle inside the back of the palm, so that hand needs a new grip or elbow, not a wrist turn.

Hand contact (grip)

A hand holds the rifle with its palm and the palm sides of its fingers. clearance is usually run with the palms and fingers left out, since a grip touches the rifle there. That also hides a hand on the wrong side. grip checks the contact itself, for each hand:

Each finger segment's palm side is the side it curls toward. The thumb's pad faces sideways, so its contacts count toward the palm side's depth only. The reply gives each hand's touching (some part within hold_within_cm), holding (touching, the palm facing the rifle and its surface within palm_within_cm), palm_gap_cm, palm_faces_rifle, palm_contact_cm, back_contact_cm, where the back contact is, and bad. With hold true, a hand that is not holding breaks a rule. solve takes {"type": "grip"} as a goal and scan_clip as a check. On the sample rig, a hand turned 180 degrees about its forearm fails it. So does the idle grip: the left thumb sits 2.8 cm inside the handguard, the right palm presses 1.2 cm into the pistol grip, and the trigger finger's back sits 0.8 cm inside the trigger guard. The sample stays as it is, so the benchmark's numbers keep their meaning.

Motion: scan and fix clips

scan_clip plays a clip frame by frame and runs checks on each frame. The checks are the solver's goals (clearance, anatomy, grip, faces_eye, visible, on_screen, barrel) and three more:

• contact: a point of the hand on its mark, such as a fingertip on the charging handle (a, b, max_cm)
• hold: how far a hand drifts on the rifle from its grip at ref_s (side, max_cm)
• pop: a sudden jump, as the fastest bone speed between frames (bones, max_cm_per_s)

Any check takes during: [from_s, to_s]. fix_clip then mends a copy of the clip:

• a pop: it blends the jumping frames again from the good frames round them
• a hold: it puts the hand back on its grip by arm IK
• a contact: it moves the wrist until the point touches its mark
• clearance: it swings each elbow about the shoulder to wrist line by the least angle that clears, wrist kept, and eases that swing over the neighbouring frames
• anatomy: it swings the elbow the same way until the elbow sits under the shoulder and inside its bend. Then it turns the wrist back inside its limits and each finger joint back inside its range. It never turns a wrist so far that the rifle goes into the back of the hand; a wrist it cannot mend that way stays as it was, and the scan after says so. Turning the wrist turns the hand on its grip, so add a hold check when the grip must stay exact.
• grip: not mended; fix_clip reports it before and after. A wrong-side hold needs a new grip.

It reports the scan before and after. It also lists the frames where a hand must be somewhere its arm cannot reach, since only a new pose can mend those.

examples/motion_test.py records a clip on the sample rig with two common faults. The rifle rolls 75 degrees and back, keyed only at its ends, so the hands drift off the rifle between keys. One frame also jumps 15 cm. The scan and the fix gave these numbers:

The fix changed 34 of 43 frames, and every check passed after it. It also flagged 6 frames where the left arm fell 0.46 cm short of its grip. That still passed the 0.5 cm limit. (Before 0.3.1 the clearance read 0.0 cm: the corner points missed the forearm inside the rifle.)

Install

You need Blender and Python 3.10 or newer. I tested it on Windows 10 with Blender 5.2.2 and Python 3.14. I have not tested macOS, Linux or older Blender versions yet.

uvx poselab-mcp

or pip install poselab-mcp and run poselab-mcp.

Add it to Claude Code:

claude mcp add poselab -- uvx poselab-mcp

or to any MCP client's configuration:

{
  "mcpServers": {
    "poselab": {
      "command": "uvx",
      "args": ["poselab-mcp"],
      "env": { "POSELAB_BLENDER": "C:/Program Files/Blender Foundation/Blender 5.2/blender.exe" }
    }
  }
}

Settings

Rigs

The built-in sample (load_rig {"rig": "sample"}) needs no files. Pose Lab builds it in Blender from code: two arms with Unreal mannequin bone names hold an AR-style rifle with a charging handle that slides back.

Your own rigs come from FBX files: the arms mesh, an idle pose, the rifle, and clips. Describe them in a rigs.json (copy examples/rigs.example.json) and point POSELAB_RIGS at it. Clips can be FBX animations on the same skeleton, or <clip>.pose.json bone data: {"fps": 30, "frames": [{"bone": [[x, y, z], [w, x, y, z]], ...}, ...]}, local location and rotation per bone on the idle armature. (Blender misreads an FBX animation it exported itself when it imports it again; bone data avoids that. describe reports each FBX clip's skeleton fit.)

Safety

• Pose Lab only reads your rig and clip files. It writes renders, saved clips and its log, and only inside POSELAB_OUT.
• The Blender worker listens on 127.0.0.1 only, on a free port, and answers only requests that carry the session's random token. It runs only Pose Lab's own commands.

How it works

• poselab_mcp/server.py: the MCP server (the official Python SDK, stdio).
• poselab_mcp/worker_client.py: starts one headless Blender on the first call and keeps the rig loaded.
• poselab_mcp/blender/lab.py: inside Blender: the rig, the frames, the measures, the IK, the solver, the renders.
• poselab_mcp/blender/sample.py: the built-in sample rig.

Test

python examples/selftest.py

It starts the server as an MCP client does and loads the sample rig. Then it replays the question above: turning alone never shows the port, and turning and moving does. The contact sheet lands in ~/.poselab/renders/sheet.png.

python examples/motion_test.py

It records the faulty clip described above, scans it, fixes it, and saves roll_fixed.pose.json and roll_fixed.fbx in ~/.poselab/clips/.

blender -b -P examples/anatomy_faults.py

It puts one known fault at a time on the sample and fails if a check misses it: a finger kinked sideways, a hand twisted against its forearm, a hand inside a flat face, a fingertip-only touch, and a rigs file with a byte order mark. These come from a real rig's benchmark (below).

Benchmark

benchmarks/ asks whether a model poses the rig better with Pose Lab's measurements than with renders alone. It runs five tasks on the sample rig and grades them with Pose Lab. A scripted oracle and a do-nothing control check the graders. See benchmarks/README.md.

benchmarks/runs/2026-10-09-toangtown-m24 tests the checks themselves on a real game rig: 8 poses of a hand on a magazine, 7 with a known fault. Pose Lab 0.3.0 caught 5 and read clipping at 40% of its depth; 0.3.1 catches all 7 with the depths exact.

License

MIT