@kamiazya/whiteboard

A collaborative Excalidraw canvas for Claude Code, Codex, and Gemini CLI. Draw with your AI agent to align on specs, architecture, and workflows — directly on a shared real-time whiteboard.

How whiteboard works

You and your agent both reach the same Excalidraw canvas — they talk, the agent acts, skills shape the prompts. The kamiazya/whiteboard plugin packages three skills and a Whiteboard MCP server together; the agent calls MCP tools via stdio and the daemon syncs the canvas to your browser over WebSocket.

@kamiazya/whiteboard-mcp runs a live Excalidraw canvas in your browser and exposes MCP tools so Claude Code, Codex, Gemini CLI, or any MCP-capable agent can draw, annotate, and refine diagrams alongside you. Canvases live locally under ~/.whiteboard/, sync over WebSocket, and round-trip with stock .excalidraw JSON.

Related MCP server: Excalidraw MCP App Server

Reach for whiteboard when…

• You're aligning with your agent on a design and text alone keeps drifting. Sketch the request flow once, ask the agent to fill in the missing edges, point at the diagram instead of re-explaining.

• You're reviewing a change and want to mark up the architecture together. Open an existing workspace, ask the agent to add the new path, compare against the previous frame, export a PNG for the PR description.

• You're writing docs or onboarding material and want a reusable diagram. Drive the agent to produce the diagram, save the .excalidraw, drop the PNG into the doc — open it again later in excalidraw.com when something needs updating.

The same workflow works across any scenario — the agent draws boxes, arrows, and labels on a fresh canvas:

Quick install

Claude Code

In a Claude Code session, run:

/plugin marketplace add kamiazya/whiteboard
/plugin install whiteboard@whiteboard-marketplace

This installs the MCP server and the bundled /drawing-visuals, /coauthoring-visuals, and /auditing-workspaces skills in one step.

claude mcp add whiteboard -- npx -y @kamiazya/whiteboard-mcp@latest

Codex

In a Codex session, run:

codex plugin marketplace add kamiazya/whiteboard

Then open /plugins, choose kamiazya Whiteboard → whiteboard → Install plugin, and restart Codex. This installs the MCP server and the bundled skills in one step.

Add to ~/.codex/config.toml:

[mcp_servers.whiteboard]
command = "npx"
args = ["-y", "@kamiazya/whiteboard-mcp@latest"]

Gemini CLI

gemini extensions install https://github.com/kamiazya/whiteboard

Add to ~/.gemini/settings.json:

{
  "mcpServers": {
    "whiteboard": {
      "command": "npx",
      "args": ["-y", "@kamiazya/whiteboard-mcp@latest"]
    }
  }
}

Verify

In your agent session, ask it to call canvas_create({ slug: "smoke" }). The first call opens a Chromium tab pointed at the canvas and creates ~/.whiteboard/{workspaceId}/.

Bundled skills

Three opinionated SKILL.md packs ship inside the npm package. The recommended plugin install above wires them up automatically — no manual linking. If you instead used claude mcp add, the Codex CLI snippet, or npx, link them yourself per docs/development.md#bundled-skills-install.

Example transcript

You    Use whiteboard to sketch the request flow for our auth service:
       client → API gateway → token service → DB. Highlight where caching lives.

Agent  cid = canvas_create({ slug: "auth-flow" }).id
       annotate_batch({ canvasId: cid, annotations: [ /* 4 service boxes + arrows */ ] })
       annotate({ canvasId: cid, type: "text",
                  target: { x: 240, y: 360 },
                  text: "cache lives here" })
       export_png({ canvasId: cid })

       Drew a 4-stage flow on the auth-flow canvas. Cache callout placed
       between API gateway and token service. PNG attached.

The agent returns the export_png result as an MCP ImageContent, so the next turn can reason about what was actually drawn — closing the loop between prompt and pixels.

Documentation

Limitations

• Live drawing and PNG export require a Chromium browser tab connected over WebSocket.

• The published transport is stdio. The HTTP MCP endpoint (pnpm mcp:http:dev) is for local development.

See docs/configuration.md for sandbox quirks.

License

MIT