Pose Lab MCP server

Pose Lab

<!-- mcp-name: io.github.hpdkhoa/poselab-mcp -->

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.

Shortened. The full README is on GitHub.