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Pose Lab

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

The built-in sample rig: four Blender views of first-person arms holding a rifle

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

Tool Answers
list_rigs, load_rig, describe the rigs, the frames, the sign rules, named points, clips, moving parts
pose_idle, pose_clip, move_part, snapshot put the rig in a pose: a clip at a time, the carrier drawn back, saved poses
move_gun roll, swing, pitch and move the rifle; the hands keep their hold by arm IK
reach a wrist onto a point by arm IK (try elbow poles to clear a forearm)
where, distance positions in a named frame
clearance how deep the rifle sits inside a forearm, palm or finger, and where
faces_eye, visible, screen how squarely a surface faces the eye, how much of it the eye sees, where it falls on screen
solve searches rifle moves against goals; reports each goal and how often any sample met it
render a contact sheet: the player's eye and outside views, each tile labelled as a Blender view
record_clip, load_clip a clip from keyed poses, or from a file: .pose.json, FBX or BVH
scan_clip every frame against checks; the worst value, when, and the time spans that fail
fix_clip mends what fails and reports the scan before and after, and what no fix can reach
save_clip writes a clip as .pose.json bone data and as FBX for a game engine

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.

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, 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

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:

Check Before After
left hand drift on the rifle 1.76 cm 0.48 cm
right hand drift on the rifle 1.14 cm 0.49 cm
fastest hand speed (the pop) 450 cm/s 33 cm/s
clearance 0.0 cm 0.0 cm

The fix changed 26 of 43 frames, and every check passed after it. It also flagged 5 frames where the left arm fell 0.46 cm short of its grip. That still passed the 0.5 cm limit.

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

Variable Meaning
POSELAB_BLENDER Blender's executable, if it is not on the PATH or in the usual install folder
POSELAB_RIGS a rigs.json describing your own rigs (see examples/rigs.example.json)
POSELAB_OUT the only folder Pose Lab writes to (renders, saved clips, the worker's log); default ~/.poselab

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/.

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.

License

MIT

Metadata

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