
Pose Lab
io.github.hpdkhoav0.2.0Updated Oct 8, 2026
Measured spatial answers for posing first-person arms and a rifle in Blender
Overview
Lets an assistant measure and pose first-person arms and a rifle in Blender, returning numbers for clearance, visibility and reach instead of guesses.
- What it does
- Pose Lab drives a headless Blender worker to answer spatial questions about a first-person arms-and-rifle rig. Tools list and load rigs, set poses, move the gun or a hand by arm IK, and report positions, distances and how deep the rifle clips into a forearm, palm or finger. It measures how squarely a surface faces the eye and what the eye sees, searches rifle moves against goals with a solver, and scans or mends animation clips frame by frame. It can also render a labelled contact sheet and save clips as bone data or FBX.
- When to use it
- Use it when posing or checking first-person weapon animations in Blender and you need measured answers rather than visual judgement, for example whether a turn can ever show the ejection port, whether a finger sits inside the receiver, or which frames of a clip drift or pop. It suits rigs described by FBX files or the built-in sample rig.
- Requirements
- Blender and Python 3.10 or newer on the same machine; tested on Windows 10 with Blender 5.2.2 and Python 3.14, with macOS, Linux and older Blender untested. Install via uvx or pip and run as a local stdio process. Optional environment variables: POSELAB_BLENDER for the Blender executable, POSELAB_RIGS for a rigs.json describing your own FBX rigs, and POSELAB_OUT for the output folder, which defaults to ~/.poselab.
Installation
In SourceWeft
- Open Pose Lab in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
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
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, cmview: 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 atref_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:
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.
or pip install poselab-mcp and run poselab-mcp.
Add it to Claude Code:
or to any MCP client's configuration:
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
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.
It records the faulty clip described above, scans it, fixes it, and saves roll_fixed.pose.json and roll_fixed.fbx
in ~/.poselab/clips/.
License
MIT
Source: README.md at commit 3a680b5
Tools
0Version history
1- v0.2.0LatestOct 8, 2026


