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Blender Optics Simulator

by emircbnglversion 0.24.4i★ –iRuns on your computer
Registry nameio.github.emircbngl/blender-optics-simulator

Install

Overview

Description from the maker (original English)

Build, align & render a real optical bench in Blender; drivable by an AI agent over MCP.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

  • Connection: Runs on your computer
  • Transport: stdio
  • Category: Design, images & audio

Install

Pick the AI app you use, then copy the settings.

Before you install

  • Basic checks: 1 of 1 passed
  • Runs on your computer with your user’s permissions (files, network, apps).
  • You fill in yourself: OPTICS_BRIDGE_PORT, OPTICS_BRIDGE_HOST

You need

  • PyPIPython’s uv installed (for the uvx command)

Which app do you use?

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "blender-optics-simulator": {
      "command": "uvx",
      "args": [
        "blender-optics-mcp"
      ],
      "env": {
        "OPTICS_BRIDGE_PORT": "your-value",
        "OPTICS_BRIDGE_HOST": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add blender-optics-simulator --env OPTICS_BRIDGE_PORT=your-value --env OPTICS_BRIDGE_HOST=your-value -- uvx blender-optics-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "blender-optics-simulator": {
      "command": "uvx",
      "args": [
        "blender-optics-mcp"
      ],
      "env": {
        "OPTICS_BRIDGE_PORT": "your-value",
        "OPTICS_BRIDGE_HOST": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "blender-optics-simulator": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "blender-optics-mcp"
      ],
      "env": {
        "OPTICS_BRIDGE_PORT": "your-value",
        "OPTICS_BRIDGE_HOST": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

  • OPTICS_BRIDGE_PORT env
    TCP port of the add-on's localhost bridge inside Blender (Optics > Simulation > Start MCP Bridge).
  • OPTICS_BRIDGE_HOST env
    Host of the add-on bridge.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

  • ✓ Pass

    Maker matches the repo

    The registry name was verified with the GitHub account emircbngl, which owns the repo

  • … Not checked yet

    Still maintained

    We have not read this repo from GitHub yet

  • … Not checked yet

    Has a licence

    We have not read this repo from GitHub yet

  • – Not applicable

    Endpoint responds

    This one runs on your computer; there is no internet endpoint

  • – Not applicable

    Sign-in with OAuth

    Runs on your computer and uses local settings instead

  • … Not checked yet

    No hidden instructions in tool descriptions

    Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Design, images & audioi

  • More stars than 0% of the other 2754 servers in this category
  • Published to the registry more recently than 16% of the other 2754 servers in this category
  • Basic checks equal to or better than 100% of the other 2754 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Blender Optics Simulator safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.24.4) reached the registry 4 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

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README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Blender Optics Simulator

An optical bench you lay out in Blender, trace with real optics, and can hand to an AI agent.

Place lasers, mirrors, lenses, waveplates, gratings, crystals and detectors in 3-D. A live engine traces the beam through them — rays, Gaussian beams, polarization, dispersion — mounts everything on real opto-mechanics, and renders it in Cycles. The whole optical state is readable and writable over a localhost MCP bridge, so an agent works from measured geometry instead of guesses.

Sixteen seconds, rendered from a scene the add-on built. Full-quality MP4 .


Install

Requires Blender 4.2 LTS or newer (4.2+ / 5.x).

One-click, keeps itself updated. Open the [install page](https://emircbngl.github.io/blender-optics-simulator/) and drag the *“⤓ Drag this into Blender to install”* button onto an open Blender window. That installs the add-on and subscribes you to updates in one gesture. Turn on *Edit ▸ Preferences ▸ System ▸ Network ▸ Allow Online Access* first.

From a zip. Download optical_alignment_sim- .zip from Releases and use *Edit ▸ Preferences ▸ Add-ons ▸ Install from Disk…*. Updates then come from the add-on's own Updates panel.

Open the Optics tab in the 3-D viewport sidebar (press N).

Quick start

  1. Setup ▸ Browse Examples… — pick *Michelson* to get a complete bench.
  2. Simulate ▸ Trace — press Live. Move any part and the beam follows.
  3. Setup ▸ Element — select an optic and change what it is: focal length, glass, coating, wavelength. Expand More for the rest.
  4. Place ▸ Mount & Adjustment — put it on a real mount and turn the knobs, with − / + steps.
  5. Inspect ▸ Optical Report — read power, polarization, path length and alignment error per detector; Align All walks the mounts until the beam lands where it should.

Headless, the same thing from Python:

import optics_api                                  # inside Blender: blender -b --python your.py

optics_api.build_example("michelson") # a full bench in one call optics_api.set_mount("MI_M_fixed", "KM100") # put a mirror on a kinematic mount optics_api.set_dof("MI_M_fixed", "TIP", steps=40) # turn a knob: the beam walks off optics_api.align_element("MI_M_fixed") # and back: 2.51 -> 0.0012 mrad print(optics_api.inspect_beam("MI_D")) # power, w(z), polarization, coherence

examples/ holds runnable scripts: michelson.py, mach_zehnder.py, agent_align.py, bell_entanglement.py, hong_ou_mandel.py.

What it does

  • Traces a real beam. Ray paths plus Gaussian-beam propagation, Jones/Stokes polarization, Fresnel losses, dispersion, nonlinear conversion, interference and wavefront error. → what is modelled, and what is not
  • 35 element types, 26 one-click benches. Mirrors through OPAs, prisms, gratings, crystals, spectrometers, adaptive optics. → element reference · full feature list
  • Mounts on real hardware. Kinematic mounts, posts, cage systems, lens tubes and rails, with mechanical limits and collision checks. → hardware
  • Measures like a bench. Detector power and polarization, beam profiles, path length, group delay and GDD, spectra, wavefront sensors. → dispersion, cylinders and spectra
  • Aligns itself. Influence-matrix solvers walk the mounts: re-centre a beam, null a tilt, close an adaptive-optics loop.
  • Renders what you built. Cycles/EEVEE with detailed optomechanics, animation renders, and SVG schematics. → how beams are drawn

A mirror knocked 2° out of alignment, then one align_element() call: pointing residual 7.02 → 0.0008 mrad. examples/agent_align.py reproduces it headlessly.

Drive it with an AI agent

The add-on exposes its full state as JSON over a localhost bridge and ships an MCP server, so an agent can read the bench and act on it:

get_state()   → every element's pose, ports, mount limits, beam path, detector readings

↓ decide set_param() · place_relative() · set_dof() · align_element() · ao_close_loop() · render() ↓ the beam re-traces get_state() → read the result, not a guess

Start it from Present ▸ Tools & Integration ▸ Start MCP Bridge. → agent guide · MCP server · tool list

Physics, honestly

Every push runs the physics: 341 textbook checks (Malus, Fresnel, Snell, the grating equation, Gaussian ABCD, Zernike orthonormality, energy conservation) plus a 618-check regression suite on both Blender 4.2 and 5.x. The core formulas were also verified against an external symbolic and numerical oracle; where that has not been done, the code and the docs say so. Every run builds the same benches in millimetre and metre scenes and requires the readouts to agree.

What is *not* claimed matters as much: this is a chief-ray engine with wave-optics overlays, not a full-wave solver. Thin elements carry no thickness, a grating has no blaze-efficiency model, and anything phenomenological says so where you read it. Model limits are written next to each feature.

→ scope and limits · element-by-element provenance · where the data comes from

Documentation

Features, examples, release historyThe long version of this page
CapabilitiesEvery panel, API call and MCP tool
Optical elementsPer-element model, parameters and provenance
ScopeWhat the engine does and does not simulate
Dispersion, cylindrical lenses, spectraGratings, white light, group delay, spectrometers
Realistic hardwareMounts, cages, rails and render detail
Beam renderingHow baked beams are drawn, and what that is not
Data sourcesCatalog and material provenance
Agent guide · MCP serverDriving the bench from outside
CHANGELOGWhat changed in each release

How to cite

A machine-readable CITATION.cff is included, so GitHub shows a Cite this repository button with ready-to-paste APA / BibTeX.

@software{cobanoglu_blender_optics_simulator,

author = {Çobanoğlu, Muhammet Emir}, title = {Blender Optics Simulator}, year = {2026}, version = {0.31.0}, doi = {10.5281/zenodo.20778997}, license = {GPL-3.0-or-later}, url = {https://github.com/emircbngl/blender-optics-simulator} }

The DOI above is the *concept* DOI and always resolves to the latest version; each release also mints its own version DOI (listed in CITATION.cff).

License & credits

GPL-3.0-or-later — see LICENSE. Vendor CAD and meshes are not included and remain the property of their owners; this project ships original metadata, procedural geometry and tooling.

Contributors

  • Tengfei Ma — ShanghaiTech University · ORCID 0009-0008-4556-4682 · @Harca-Yita. Reports from a working optical bench in #1 drove wavelength-true beam colours and the shutter, the unit-scale work, shaped apertures, reflection at the coated mirror face, the Porro prism and polished mirror substrates, the OPA and group-delay work, and the groove-oriented grating, cylindrical lens and spectrum detector.

Built in the spirit of Bigweld's maxim from *Robots* (2005) — "See a need, fill a need."

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