maryslab
MCP server for computational color science, offering 32 tools for spectral palette design, illuminant robustness certification, metamerism analysis, and color vision test generation.
README
<div align="center">
<img src="docs/assets/logo.svg" width="110" alt="Mary's Lab: an outlined eye whose iris is the only color" />
Mary's Lab
A computational color science laboratory. She knows everything about color. She has never seen it.
</div>
Named for Frank Jackson's thought experiment: Mary, the scientist who knows every physical fact about color but has only ever seen black and white. This lab works the way Mary does. Color arrives as spectra, matrices, and proofs, and the instruments built here do things the field's tooling has not done before.
What lives here
32 MCP tools any AI agent can call, over two engines that must agree: a TypeScript reference engine and a C++20 core behind a stable C ABI, held together by 401 shared golden vectors and a metamorphic relation suite that runs against both.
The interesting tools are the ones without precedent as software. Every existing color tool is forward and point-wise: spectrum in, number out. These work the other three directions:
| Instrument | What it does that nothing else does |
|---|---|
certify_illuminant_robustness |
Guaranteed lower bound on palette discriminability over an entire convex family of illuminants, not a spot check |
design_spectral_palette |
Designs reflectance spectra (not colors) whose separation survives observers and illuminants jointly |
design_discrimination_test |
Computes optimal color-vision test stimuli; plates have been built by trial and error for a century |
synthesize_adversarial_illuminant |
Finds the physically realizable light that breaks a palette; the attack to the certificate's defense |
audit_colormap_topology |
Persistent-homology certificate of the features a colormap invents or destroys, per observer, CVD included |
sample_metamers + map_metamer_stratification |
Walks the convex metamer set and maps where its combinatorial structure changes across color space |
audit_spectrum_provenance |
Measurement forensics: is this spectrum measured, or interpolated and passed off as measured? |
generate_metamer_benchmark |
Physically realizable confusion pairs: identical under one light, split under another |
Plus a correctness suite (crosscheck_color_implementations,
generate_conformance_vectors) that metamorphically tests any color library
against algebraic identities. It found a real bug in this repo's own engine
on its first run.
<div align="center"> <img src="docs/assets/metamer-atlas.svg" width="30%" alt="Many metameric reflectance curves collapsing to a single color swatch" /> <img src="docs/assets/design-discrimination-test.svg" width="30%" alt="Ishihara-style dot field generated from engine-computed confusable pair" /> <img src="docs/assets/audit-colormap-topology.svg" width="30%" alt="Lightness profiles and colormap strips for viridis and jet" /> <br/> <sub>Every figure in this repo and on the site is generated by the instruments themselves. No stock art.</sub> </div>
Quick start
git clone https://github.com/JeetuSK0808/maryslab
cd maryslab && npm install
cd mcp && npm test && npm run build
claude mcp add maryslab -- node "$(pwd)/dist/server.js"
Then ask your agent to certify a palette, design a spectrum, or audit a colormap. Full tool reference: docs/mcp-tools.md.
Architecture
flowchart LR
A[AI agents\nClaude Code, any MCP client] -->|MCP stdio| B[mcp/\nTypeScript server\n32 tools, zod schemas]
B --> C[TS reference engine\nmcp/src/engine]
B -.->|when built| D[core/\nC++20 engine\nstable C ABI]
C <-->|401 golden vectors\n+ metamorphic relations| D
E[data/\ningestion, quality gates] --> B
F[web/\nAstro site] --> C
The two engines are not allowed to drift: core/tests/golden/conformance.csv
is generated from the TypeScript engine and checked by the C++ test suite,
and the same metamorphic relations (round trips, metric axioms, white-point
preservation, spectral linearity) run against both. 171 TS tests, 79 native
tests, all green.
The honesty rules
This lab's differentiator is that caveats travel with results.
- CVD compensation remaps for discriminability. It never claims to restore what dichromacy removed.
- Isotope matches and forensic scores are decision support, never authoritative identification. The forensics tool states in its own output that it was calibrated on synthetic negatives.
- Infeasible constraints fail loudly with the achieved bound, never silently relaxed.
- Certificates report when their own grid is too coarse to certify anything
(
grid_sufficient: false) instead of printing a hollow zero. - Papers are in preparation. Nothing here cites a preprint that does not exist. See docs/PRD.md §5 for the ideas we cut because the math did not hold.
Repository map
| Path | What | Verify with |
|---|---|---|
mcp/ |
MCP server + TS reference engine | cd mcp && npm test |
core/ |
C++20 engine, C ABI in include/mary/mary.h |
cmake --preset release && ctest --preset release |
data/ |
Spectral ingestion pipeline, quality gates Q1-Q6 | cd data && uv run pytest |
web/ |
The lab's website (Astro) | cd web && npm run build |
bindings/ |
node N-API, WASM, Python scaffolds | builds in CI |
papers/ |
Paper threads with pinned artifacts | in preparation |
docs/ |
PRD, architecture, tool reference, ABI rules | start at docs/PRD.md |
Contributing
The highest-value contribution is a dataset source adapter with a verified
license (see docs/dataset.md). Ground rules in
CONTRIBUTING.md: conventional commits, coverage stays at
80 percent, golden vectors change only through a golden-update PR, and
scientific claims cite their sources.
License
Code: Apache-2.0. Dataset records carry per-source licenses, tracked in
data/catalogs/sources.yaml.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.