Doodleworks MCP

Turn any idea (a blog post, an article, an X post) into hand-drawn "Tinku" illustrations that explain the key concepts, right inside your AI host.

_{Bring your own image-API key (OpenAI or Gemini) · local stdio server · flip through, regenerate, and download, all in your host's chat.}

Quick start · Add to your host · Using it · Parameters · The viewer · Examples · Configuration · Build from source · How it works

Doodleworks turns a single idea (or a whole blog post, article, or X post) into clean line illustrations that explain its key concepts, one idea per picture. It never draws the topic literally. Instead, it pulls out each concept and reinvents it as a low-tech contraption that Tinku, the app's own character, is physically operating: confident black lines on a pure-white background, with a few neat red/orange/blue handwritten labels.

Ask your AI host for a set of illustrations, and Doodleworks renders them and opens an interactive viewer right in the chat: flip through, regenerate any image you don't like, and download the PNGs.

_{The interactive viewer in Claude Desktop: browse the set, regenerate any image, and download PNGs (with an optional title burned in).}

✨ Highlights

• 🖐️ Hand-drawn, one idea per picture: clean black line art on white with a few red/orange/blue labels; never a literal chart or diagram.
• 🧩 Concepts, not clip art: each key idea becomes a low-tech contraption that Tinku, the app's recurring character, physically operates.
• 🖼️ Interactive viewer in your chat: browse, zoom, regenerate any single image, and download PNGs, inline in supported hosts.
• 🔑 Bring your own key: OpenAI or Gemini. The key stays server-side and is never sent to the viewer or the iframe.
• ⚡ Zero infrastructure: a local stdio server you launch with one npx line. No clone, no build, no database.

🚀 Quick start

No clone and no build required: npx fetches the published doodleworks-mcp package from npm and runs it. You'll need an image-API key to render (none is needed just to install).

1. Get an image key. Use one of:

• OPENAI_API_KEY: OpenAI GPT Image (the default provider)
• GEMINI_API_KEY (or GOOGLE_API_KEY): Gemini 3 Pro Image ("Nano Banana Pro")

New here? Start with OPENAI_API_KEY: it's the default, and every example below was generated with it. Set just one; you don't need both.

2. Add it to your AI host. Drop this into your host's MCP config (Claude Desktop's claude_desktop_config.json shown; see Add it to your AI host for every other host):

{
  "mcpServers": {
    "doodleworks-mcp": {
      "command": "npx",
      "args": ["-y", "doodleworks-mcp"],
      "env": { "OPENAI_API_KEY": "sk-..." }
    }
  }
}

3. Ask in plain language. Restart the host, then say:

Use doodleworks to create a set of 6 illustrations explaining how a heat pump heats your home, for homeowners, one idea per image.

[!TIP] The model writes each illustration's prompt for you. You just describe the topic. In a graphical host the viewer opens with the gallery; in a terminal host you'll get tool output only (a text summary, not the rendered images).

🔌 Add it to your AI host

Doodleworks is an MCP App: it exposes tools and an interactive UI. Every host below can run the tools, but the inline viewer (the whole point) only renders in hosts that support MCP Apps UI.

[!TIP] Want the inline viewer? Use Cursor, VS Code, Claude Desktop, or Goose. Claude Code and Windsurf run the tools but can't show the viewer (you'll get tool output instead).

[!NOTE] Every config below uses the published package (npx -y doodleworks-mcp), so there's no clone and no build. Hacking on your own checkout instead? Swap the command for npx -y tsx /ABSOLUTE/PATH/doodleworks-mcp/main.ts --stdio (see Build from source). Use whichever image key you exported.

{
  "mcpServers": {
    "doodleworks-mcp": {
      "command": "npx",
      "args": ["-y", "doodleworks-mcp"],
      "env": { "OPENAI_API_KEY": "${env:OPENAI_API_KEY}" }
    }
  }
}

{
  "inputs": [
    { "type": "promptString", "id": "openai-api-key", "description": "OpenAI API key", "password": true }
  ],
  "servers": {
    "doodleworks-mcp": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "doodleworks-mcp"],
      "env": { "OPENAI_API_KEY": "${input:openai-api-key}" }
    }
  }
}

extensions:
  doodleworks-mcp:
    type: stdio
    name: doodleworks-mcp
    enabled: true
    cmd: npx
    args: ["-y", "doodleworks-mcp"]
    envs:
      OPENAI_API_KEY: "sk-..."
    timeout: 300