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brickscope

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    • License MIT

    CLI and MCP server for LEGO recognition — identify parts, sets, and minifigures from images

    Package Exports

    • brickscope
    • brickscope/dist/mcp/index.js

    This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (brickscope) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.

    Readme

    Brickscope

    Identify LEGO parts, sets, and minifigures from images — as a CLI tool or an MCP server for AI assistants.

    Powered by the Brickognize API and Rebrickable.

    Huge thanks to Piotr Rybak for creating the Brickognize service and making LEGO recognition accessible to everyone!

    CLI

    npm install -g brickscope
    
    brickscope identify photo.jpg --type part
    brickscope part 3001 --color Black
    brickscope set 75192
    brickscope minifig fig-012805

    Or run without installing: npx brickscope identify photo.jpg

    Full CLI documentation

    MCP Server

    For AI assistants (Claude, Cursor, etc.), add to your MCP config:

    {
      "mcpServers": {
        "brickscope": {
          "command": "npx",
          "args": ["-y", "brickscope", "mcp"],
          "env": {
            "REBRICKABLE_API_KEY": "your-key-here",
            "BRICKOGNIZE_CACHE": "sqlite"
          }
        }
      }
    }

    Full MCP documentation

    Configuration

    Config file (CLI)

    brickscope config init

    Creates ~/.config/brickscope/config.json with your Rebrickable API key and cache settings.

    Environment variables

    Variable Default Description
    REBRICKABLE_API_KEY Free API key from rebrickable.com/api. Required for lookup tools.
    BRICKOGNIZE_CACHE none Cache mode: none, memory, or sqlite

    Environment variables take priority over the config file.

    Features

    • Image recognition — identify parts, sets, minifigures, and stickers from photos
    • Batch processing — identify multiple images in parallel
    • Part lookup — colors, set appearances via Rebrickable
    • Set inventory — full parts list, year, theme, piece count
    • Minifigure lookup — details and set appearances
    • Caching — in-memory or SQLite cache for Rebrickable API responses
    • Config file — save API key and preferences once, use everywhere

    Examples

    See the examples folder for prompt templates.

    Development

    npm install
    npm run build
    npm run dev           # Watch mode
    npm test              # Unit + integration tests
    npm run lint          # ESLint
    npm run format        # Prettier

    License

    MIT