OptiVibe MCP server

optivibe-mcp

optivibe-mcp is an experimental MCP server that provides tooling for a coding agent — such as Claude Code — to interface with Zemax OpticStudio.

One unattended run: a 60× objective reworked into a 10× / NA 0.45 apochromat, polychromatic Strehl ≥ 0.935 at every field point. How it was done and measured.

It exposes OpticStudio operations as typed MCP tools: loading designs, editing lens data, running analyses, optimization, and tolerancing, driven through the ZOS-API so the agent doesn't have to write raw API code. Alongside the tools is a reference layer the agent can query — operand and glass lookups, and full-text search over the OpticStudio manual.

Install it with pip install optivibe-mcp (on PyPI); the server is also listed in the official MCP Registry as io.github.chuang44-tiff/optivibe-mcp. See Install.

What's in it

the ZOS-API. Each returns a uniform result envelope rather than raising, so the agent checks a read-back value instead of assuming a call succeeded. Beyond spherical surfaces it authors aspheres, coordinate breaks, fold mirrors, diffraction gratings, and gradient-index media. For a settled lens it can also show which elements carry the colour and field-curvature terms and trial glass swaps against a control (see Glass tools).

• Tools (optivibe-mcp, in packages/optivibe-harness/) — more than 80 typed tools that drive OpticStudio over

search, to help ground the agent's choices. Engine-free and license-free; its data is built locally (see Build the reference data).

• Reference layer (optivibe-reference) — operand and glass lookups plus manual

The project ships code only. No vendor data (glass catalog, manual text, operand descriptions) is included — you generate it from your own licensed OpticStudio install.

Demos

Each demo ships its brief, the agent's stage log, the starting lens and the result lens, with a script that re-measures them: see demos/.

An agent reworks a 60× objective into a 10× / NA 0.45 apochromat, unattended One run with no human in the loop produced a 10× / NA 0.45 objective with a polychromatic Strehl ratio of 0.935 or better at all four field points, measured afterwards by a separate script.

A local model does the same job with OptiVibe's skills and MCP server Qwen3.8-Flash-Next on a local server, given a brief tuned for this task, met the same targets with a polychromatic Strehl of 0.834 or better at all four field points. The page says where it trails Opus.

An agent refines a 20× zoom, and the promotion gate holds it back One run more than halved the blur at the zoom's worst position, missed its distortion target, and the server refused to promote the result over two thin filter plates. The headline figures reproduced on a re-read of the saved file.

Does the agent design a better lens when it can see the drawing? The same lens task, run with no human in the loop until each arm had three finished lenses: every run that used the layout review produced a shorter lens than every run that worked from numbers alone (70–100 mm against 140–221 mm), and every vision lens held an on-axis Strehl ratio of 0.93 or better at all four wavelengths.

Shortened. The full README is on GitHub.