Chisel

Chisel

[](https://buy.polar.sh/polarclv4ZIuYffdbN9E9iVLmlHh1W5sxAmxvqNVqIn81048FX)

An MCP server that lets AI agents build, edit, render, and export real 3D models — from geometric primitives and boolean CSG. No diffusion, no GPU, no browser. The agent calls modeling tools, gets back a multi-view render to see its work, iterates, and exports clean .glb/.obj.

> Every model is real, editable geometry — boxes, spheres, cylinders, cones combined with > union / subtract / intersect and mirrored for symmetry. The render above (a chair > built from 9 tool calls) is produced by a pure-CPU software rasterizer — the same > thing the agent sees each step.

Why

Image/mesh diffusion models paint surfaces — you get a blob you can't cleanly edit or boolean. Chisel takes the opposite approach: give an agent a discrete, inspectable modeling API and a see-and-revise loop, and it builds real solids you can open in Blender, slice for printing, or drop into a game engine.

The hard part of 3D-by-agent isn't geometry, it's occlusion — any single view hides half the model. So Chisel renders four canonical views every step (front / side / top / iso) and hands them back as an image, so the agent reasons about the whole form, not one face.

Quick start

Run the server (stdio):

# zero-install, straight from GitHub (builds on first run)
npx -y github:EYamanS/chisel

# …or from a clone
git clone https://github.com/EYamanS/chisel && cd chisel
npm install
npm run mcp

Wire it into any MCP client (claude_desktop_config.json, .mcp.json, etc.):

{
  "mcpServers": {
    "chisel": {
      "command": "npx",
      "args": ["-y", "github:EYamanS/chisel"],
      "env": { "CSG_OUTPUT_DIR": "/absolute/path/to/exports" }
    }
  }
}

Or point at a local clone for speed:

{
  "mcpServers": {
    "chisel": {
      "command": "node",
      "args": ["/absolute/path/to/chisel/dist/server.js"],
      "env": { "CSG_OUTPUT_DIR": "/absolute/path/to/exports" }
    }
  }
}

Then just ask your agent: "model a coffee mug and export it as a glb."

Tools

| Tool | What it does | |------|--------------| | add_box add_sphere add_cylinder add_cone | Add a primitive (size/radius/height, position, rotation, color). | | transform | Move / rotate / scale an object (absolute or relative). | | union subtract intersect | Boolean CSG — fuse, carve a hole, or clip to an overlap. | | mirror | Reflect an object across X/Y/Z. Composes with booleans — build one side, mirror it. | | set_color delete select | Recolor, remove, highlight. | | get_scene | Return the scene graph as text (every object, shape, transform). | | render | Return a 2×2 multi-view PNG (front/side/top/iso) so the agent can see the model. | | export_model | Write .glb or .obj to disk; returns the path. inline:true for base64. | | reset | Clear the session to an empty scene. |

Models persist per session id (default main) for the life of the process, so an agent builds incrementally across calls. Rendering is GPU-free (a software rasterizer over the evaluated CSG triangles), so it runs anywhere Node runs — laptops, CI, containers.

A typical agent loop

add_cylinder { radius: 0.6, height: 1.2, position: [0, 0.6, 0], color: "steel" }   -> obj1
add_cylinder { radius: 0.46, height: 1.1, position: [0, 0.74, 0] }                 -> obj2
subtract     { a: "obj1", b: "obj2" }   # hollow it out                            -> obj3
render       # look at all four views, notice it needs a handle
add_box      { size: [0.16, 0.62, 0.16], position: [0.66, 0.62, 0], color: "steel" }
union        { a: "obj3", b: "obj4", name: "mug" }
render       # looks right
export_model { format: "glb" }          # -> ./exports/main-.glb

Web playground (optional)

The repo also ships an interactive Next.js playground where an OpenAI model drives the same engine in your browser, with a live 3D viewport and glTF/OBJ export:

cp .env.local.example .env.local   # add OPENAI_API_KEY
npm run dev                        # http://localhost:3000

The Demo buttons (Mug / Table / Rocket) exercise the full engine with no API key.

How it works

src/lib/scene/    types.ts        scene graph: flat list of CSG expression trees
                  operations.ts   deterministic reducer — applies one tool call
                  tools.ts        modeling tool schemas (shared by MCP + web agent)
src/lib/three/    build.ts        scene graph -> Three.js meshes (evaluates CSG)
src/lib/render/   raster.ts       headless software renderer (no GPU) -> 2x2 PNG
                  export.ts       glTF/OBJ export | png.ts encoder | font.ts labels
src/mcp/          server.ts       MCP server (stdio) | engine.ts session store
src/lib/agent/    loop.ts         web playground's render->see->revise agent loop
src/components/   Viewport.tsx    browser viewport (WebGL) + capture + export
src/app/          page.tsx        playground UI | api/agent/route.ts OpenAI proxy

The MCP server and the web playground are two front-ends over one engine — same scene graph, same CSG, same tool schemas. The MCP path is fully headless (software-rendered); the web path uses WebGL for the interactive viewport.

Development

npm run mcp         # run the MCP server from source (tsx)
npm run build:mcp   # bundle the self-contained binary -> dist/server.js
npm run dev         # web playground
npm run build       # production build of the web app

Support

Built this in the open. If it saved you time, a one-off tip keeps it maintained:

[](https://buy.polar.sh/polarclv4ZIuYffdbN9E9iVLmlHh1W5sxAmxvqNVqIn81048FX)

License

MIT © Emir Yaman Sivrikaya

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Keywords: AI 3D modeling · text to 3D · MCP 3D model generator · generate 3D models with AI · constructive solid geometry (CSG) · procedural 3D · headless glTF / GLB / OBJ export · LLM 3D-modeling agent.

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: EYamanS
• Source: EYamanS/chisel
• License: MIT

Install and usage instructions live in the source repository linked above.