chisel
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@chiselmodel a coffee mug and export as glb"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Chisel
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/intersectand 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.
Related MCP server: Blender MCP Server
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 mcpWire 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 a primitive (size/radius/height, position, rotation, color). |
| Move / rotate / scale an object (absolute or relative). |
| Boolean CSG — fuse, carve a hole, or clip to an overlap. |
| Reflect an object across X/Y/Z. Composes with booleans — build one side, mirror it. |
| Recolor, remove, highlight. |
| Return the scene graph as text (every object, shape, transform). |
| Return a 2×2 multi-view PNG (front/side/top/iso) so the agent can see the model. |
| Write |
| 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-<ts>.glbWeb 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:3000The 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 proxyThe 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 appLicense
MIT © Emir Yaman Sivrikaya
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/EYamanS/chisel'
If you have feedback or need assistance with the MCP directory API, please join our Discord server