Stickman Character MCP Server

Turns your Red-Hat-engineer stickman reference art into a posable, rigged character that any MCP-compatible coding agent (Claude Code, Claude Desktop, Cursor, etc.) can control directly — set joint angles, pick a facial expression, and render single frames or full animations (GIF/MP4). Because every frame is generated from the same parametric SVG rig, the character stays perfectly on-model across an entire video instead of drifting the way frame-by-frame image generation does.

Staying on-model

The rig is measured directly off the reference sheet rather than approximated, so a render lines up with the source art almost pixel for pixel:

• Proportions were taken from the front-view reference (1024px source, head outer radius 121px) and scaled by 0.546 onto the 400x520 canvas — spine 215px, upper/fore arm 108/120, upper/lower leg 126/127, limb stroke ~19px, head centre 133px above the shoulder fork.

• The fedora is a vector trace of the reference hat, not a hand-built approximation. It ships as normalised SVG paths (HAT_PATHS in rig.py) expressed in head-radius units and drawn via translate(head) scale(head_radius), so it rides the head through any tilt and keeps the exact brim sweep, crown pinch and band of the original.

• Palette is sampled from the art: #D51918 bright red, #A01513 mid, #7E1212 shadow, #C2C3C5 face shading, #D2D3D5 ground shadow.

• The face matches the reference conventions — the neutral face is two solid black ovals and no mouth. White-eyeball-and-pupil eyes are used only for happy/excited/surprised, and angry uses slanted wedges with gritted teeth, exactly as in the reference expression sheets.

hat_color is still fully parametric: pass any hex and the mid and shadow tones are derived from it using the reference's own 1.0 / 0.742 / 0.592 ramp.

What's inside

stickman_mcp/
  rig.py       - the skeleton: joints, forward kinematics, SVG renderer,
                 traced fedora paths, facial expressions, pose presets
  animate.py   - keyframe interpolation + export to PNG sequence / GIF / MP4
  server.py    - the MCP server itself (tools below)
pyproject.toml

Install

cd stickman_mcp
python3 -m venv venv
source venv/bin/activate
pip install -e .

This pulls in mcp, cairosvg (SVG→PNG rendering) and pillow (GIF export). GIF/PNG-sequence export needs no extra system deps; MP4 export requires ffmpeg to be installed and on your PATH.

Register it as an MCP server

Claude Desktop / Claude Code — add to your MCP config (~/Library/Application Support/Claude/claude_desktop_config.json on macOS, or the equivalent Claude Code config):

{
  "mcpServers": {
    "stickman": {
      "command": "/absolute/path/to/stickman_mcp/venv/bin/python",
      "args": ["-m", "stickman_mcp.server"],
      "cwd": "/absolute/path/to/stickman_mcp"
    }
  }
}

Or run it standalone over stdio to test:

python -m stickman_mcp.server

Tools exposed

Joints (all angles in degrees, 0 = straight down, + = clockwise)

l_shoulder, l_elbow, r_shoulder, r_elbow, l_hip, l_knee, r_hip, r_knee, neck (head tilt), spine (torso lean), hip_shift (px, horizontal), body_lift (px, vertical, negative = up).

l_ is the character's left, i.e. the viewer's right. Mirrored poses need opposite-signed knee angles (l_knee=86, r_knee=-86) so both shins bend the same way.

Style keys (per pose, not interpolated — they snap at the keyframe)

• hands — "blob" (default), "open", or "fist". Also accepts a dict for per-side control: {"r": "open"} leaves the other hand a blob.

• front_arm — "l", "r" or "both", drawing that arm over the head. Needed whenever a hand lands on the face (facepalm, thinking_pose), since the hat brim is ~1.5x the head width and would otherwise cover it.

• prop — currently "chair", drawn behind the character for sit.

Poses

idle, wave_right, wave_left, point_right, point_left, explain_hands, explain_left_hand, thinking_pose, arms_up_happy, arms_crossed, hands_on_hips, fists_up, walk_1, walk_2, run_1, run_2, jump, crouch, sit, shrug, facepalm, bow, look_up, look_down, celebrate, typing.

Expressions

neutral, happy, excited, sad, angry, surprised, thinking, wink, talking, calm.

Example: a coding agent building a short clip

render_animation(
  keyframes=[
    {"pose": "idle",          "expression": "neutral", "hold": 0.5},
    {"pose": "wave_right",    "expression": "happy",   "hold": 1.0, "transition": 0.3},
    {"pose": "explain_hands", "expression": "excited", "hold": 1.5, "transition": 0.3},
    {"pose": "idle",          "expression": "happy",   "hold": 0.5, "transition": 0.3},
  ],
  fps=12,
  out_format="mp4",
)

An agent can also skip presets entirely and hand-author a pose:

render_pose(
  joints={"r_shoulder": -90, "r_elbow": 20, "neck": -10},
  expression="excited",
)

Transitions use smoothstep easing, so poses ease in and out rather than sliding linearly between keyframes.

Notes / next steps

• The rig covers front-facing 2D poses only (matching most of the reference set). A left/right-facing profile variant — for the side-profile and walking-toward-camera references — is the natural next addition: the skeleton already supports it, but the head, face and traced hat would each need a profile variant.

• sit now draws a simple wooden chair via prop="chair". Other props would slot into _chair_svg's pattern in rig.py.

• render_animation keyframes can be produced programmatically for a "character walks across screen" shot: sweep hip_shift while alternating walk_1 / walk_2.