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One MCP server, four clients, zero translation apps open in browser tabs

"konid," a language-learning MCP server built by the author after six months of translating Japanese work emails. Unlike standard translation tools, konid returns three options per query ordered from casual to formal, explaining the cultural nuance and register of each, and it can be integrated into multiple coding environments like Claude Code, Cursor, and VS Code via a single server setup. The tool supports over 13 languages and is available as an MIT-licensed open-source project on GitHub.

read2 min views9 publishedMay 20, 2026

I built konid after translating work emails in Japanese for six months and realizing I was getting through each email but learning nothing. Same literal output every time, no sense of whether I was being too stiff or too casual, no audio to check whether I'd read the pronunciation right in my head. The specific thing konid does differently: it returns three options per query, ordered casual to formal, with the register named and a comparison of the cultural nuance between them. Not "here's your translation" — more like "here are the three ways a native speaker might say this, and here's why you'd pick each one." Audio plays through speakers via node-edge-tts, no external API key involved. The angle I want to cover here is MCP client coverage, because this is the part that took the most work and matters most to how I actually use it. konid runs as an MCP server. Install once: claude mcp add konid-ai -- npx -y konid-ai That gets you Claude Code. The same server config works in Cursor, VS Code Copilot, Windsurf, Zed, and JetBrains with their respective MCP settings. For Claude Cowork — the multi-agent workspace — you point it at the same server process. For ChatGPT, Developer mode accepts the hosted endpoint directly: https://konid.fly.dev/mcp The reason this matters: I switch between Claude Code (coding sessions), Claude Cowork (longer research), and ChatGPT depending on the task. Before, that meant context-switching to a browser tab, pasting text, getting a flat answer, closing the tab. Now the same tool is available wherever I'm already working. The language coach doesn't move; I move. I've tested it against 13+ languages including Mandarin, Japanese, Korean, Arabic, Spanish, French, and Hindi. The register distinction is sharpest in the languages that formalize it most explicitly — Japanese keigo levels, Korean speech styles, Arabic formal vs. colloquial — but it's useful in Spanish and French too where casual vs. formal lands differently depending on the relationship. MIT licensed. Source and full setup docs at https://github.com/robertnowell/konid-language-learning.

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