MCP bridge for Tesserae Studio: author e-ink widgets with an AI agent.
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# tesserae-studio-mcp > Part of the [Tesserae Studio](https://github.com/dmellok/tesserae-studio) > repo (`packages/tesserae-studio-mcp`), so the bridge stays in lockstep with > the Studio API it wraps. Published to PyPI as `tesserae-studio-mcp`. The [MCP](https://modelcontextprotocol.io) bridge for [Tesserae Studio](https://github.com/dmellok/tesserae-studio). It lets an AI agent (Claude Code, Claude Desktop, or any MCP client) **author Tesserae widgets** end to end: scaffold a widget, edit its files, lint it, mine a data schema, register it to a running Tesserae, and render it, all through a running Studio server. This is a thin stdio client. It talks to your Studio server over its local REST API (`STUDIO_URL`), so the linting, mining, registering, and rendering all run in your own Studio, which in turn drives your Tesserae. ``` scaffold_widget → write_file → lint_widget → register_widget → faithful_render → mine_data_schema ``` ## Prerequisites A running **Tesserae Studio** server (it serves the API this bridge calls, and its web UI). See the [Studio README](https://github.com/dmellok/tesserae-studio) for how to run it. Studio in turn connects to a Tesserae for live data and faithful (e-ink) render. ## Install Run this on the machine where your **agent** runs, which may differ from where Studio runs. ```bash pip install tesserae-studio-mcp ``` or from source: ```bash pip install "git+https://github.com/dmellok/tesserae-studio#subdirectory=packages/tesserae-studio-mcp" ``` Either gives you the `tesserae-studio-mcp` command. ## Configure your agent Point your MCP client at `tesserae-studio-mcp`. Example (Claude Desktop / Claude Code `mcpServers` config): ```json { "mcpServers": { "tesserae-studio": { "command": "tesserae-studio-mcp", "env": { "STUDIO_URL": "http://localhost:8770" } } } } ``` Claude Code one-liner: ```bash claude mcp add tesserae-studio -e STUDIO_URL=http://localhost:8770 -- tesserae-studio-mcp ``` - `STUDI…
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