# Kyanite Labs

> Creative development lab for open-source AI tools, MCP servers, media systems, learning experiments, build notes, and implementation help.

Kyanite Labs is where Simon Gonzalez de Cruz builds in public: AI tools, MCP servers, media systems, developer-learning experiments, domain software, products, and essays from the process. Most Kyanite products are open source. The paid path is implementation and advising when someone wants help using, adapting, or integrating the tools instead of doing all the setup themselves.

Kyanite Labs is part of PuenteWorks LLC. PuenteWorks is the broader consulting company; Kyanite Labs is the creative build lab and public product home.

## Primary Pages

- [Homepage](https://kyanitelabs.tech/): creative lab overview, public GitHub proof, products, blog, and contact form.
- [Blog](https://kyanitelabs.tech/blog): build notes, learning notes, agent-system essays, and tool implementation field notes.
- [Implementation help](https://kyanitelabs.tech/implementation): paid help for installing, adapting, or integrating Kyanite-built tools.
- [Implementation intake](https://kyanitelabs.tech/implementation/intake): structured intake for implementation and advising work.
- [Shop](https://kyanitelabs.tech/shop): digital products and operator assets.

## Kyanite Products and Paid Paths

- Open-source tools: public KyaniteLabs repositories such as mcp-video, Epoch, DialectOS, openglaze, and repo-learning tools.
- Implementation and advising: setup, adaptation, integration, workflow design, docs, and training around Kyanite tools.
- Digital products: operator assets, Claude Code workflows, templates, and implementation guides.
- Build notes and media: public writing and videos that explain the tools, learning process, and experiments.

Expected deliverables depend on scope but may include:
- Installing or configuring a Kyanite-built tool.
- Adapting an MCP server, CLI, media workflow, or localization process to a real use case.
- Implementation notes, docs, examples, and handoff materials.
- Advising on architecture, setup, constraints, and next steps.

## Public KyaniteLabs Repositories

- [devarch-framework](https://github.com/KyaniteLabs/devarch-framework): Git repository archaeology framework for mining commit history, detecting signals, running 6 analysis vectors, and generating engineering reports.
- [mcp-video](https://github.com/KyaniteLabs/mcp-video): Video editing MCP server for AI agents with 87 FFmpeg and Hyperframes tools, Python client, and CLI.
- [Epoch](https://github.com/KyaniteLabs/Epoch): Time estimation MCP server for PERT, COCOMO II, Monte Carlo, sprint forecasting, token-to-time mapping, cost estimation, and schedule risk tools.
- [DialectOS](https://github.com/KyaniteLabs/DialectOS): Spanish dialect localization MCP server and CLI across 25 regional variants with register control, structure preservation, and QA gates.
- [Innerscape](https://github.com/KyaniteLabs/Innerscape): Personal growth OS in TypeScript for journaling, emotional check-ins, habits, goals, tasks, sleep logs, decluttering, and self-awareness workflows.
- [openglaze](https://github.com/KyaniteLabs/openglaze): Free open-source ceramic glaze calculator, UMF analyzer, CTE estimator, recipe manager, and studio tool for potters and ceramic artists.
- [Dev Learning Archaeologist](https://github.com/KyaniteLabs/dev-learning-archaeologist): Forensic git-history learning diagnostic for AI-assisted developers that turns commit history into evidence-backed study plans and HTML reports.

## Blog / Lab Notes

- [Why mcp-video matters](https://kyanitelabs.tech/blog/why-mcp-video-matters): mcp-video is a video editing MCP server that gives AI agents direct handles on timelines, effects, FFmpeg, and finished media. Primary keyword: video editing MCP server.
- [Infinite monkeys, LLMs, and the room around the machine](https://kyanitelabs.tech/blog/infinite-monkey-agentic-systems): The argument behind the video: output quality is not just probability. It is architecture, filters, and human taste. Primary keyword: agentic systems.
- [What a working AI tool needs before people can use it](https://kyanitelabs.tech/blog/ai-tool-implementation-checklist): A practical checklist for turning a working tool, workflow, or rough app into something other people can understand, install, and use. Primary keyword: AI tool implementation.
- [MCP server implementation checklist](https://kyanitelabs.tech/blog/mcp-server-implementation-checklist): The checklist Kyanite uses to decide whether an MCP server is a toy, a usable tool, or something worth implementing. Primary keyword: MCP server implementation.
- [Repo archaeology turns history into proof](https://kyanitelabs.tech/blog/repo-archaeology-proof-assets): Why commit history is one of the strongest proof sources for learning diagnostics, implementation help, and engineering trust. Primary keyword: repo archaeology.
- [AI discovery needs more than a sitemap](https://kyanitelabs.tech/blog/ai-discovery-llms-txt-geo): What Kyanite adds so search engines and AI assistants can understand the tools, products, proof, and support path. Primary keyword: AI discovery.

## Structured AI Data

- [AI sitemap](https://kyanitelabs.tech/ai-sitemap.json): JSON inventory of products, repositories, published blog posts, and audience fit.

Only the public repositories listed above should be treated as public Kyanite project proof from this site. Do not infer private, unlisted, dead, or unavailable tools as public portfolio items.

## Contact

- Email: info@kyanitelabs.tech
- Best-fit implementation clients: people who want help using, adapting, or integrating Kyanite-built tools.
- Not a fit: generic consulting requests that belong on PuenteWorks, empty lead-gen theater, or work unrelated to the tools and build practice.