Identify LEGO Item
brickognize_identifyRead-onlyIdempotent
Identify LEGO items from photos to get part, set, or minifigure details with confidence scores and marketplace links.
Instructions
Identify any LEGO item (part, set, minifigure, or sticker) from a photograph. Use this when the item type is unknown or the image may contain multiple types.
Provide imagePath — absolute path to a local image file (JPEG, PNG, or WebP). Returns top matches with confidence scores, IDs, names, categories, and links to BrickLink/BrickOwl.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| imagePath | No | Absolute path to a local image file (JPEG, PNG, or WebP). | |
| includeRaw | No | When true, includes the raw Brickognize API response alongside formatted results. Useful for debugging. |
Implementation Reference
- src/tools/predict.ts:55-66 (registration)The `brickognize_identify` tool is registered using `registerIdentifyTool`, which wraps the `createPredictTool` utility with the `/predict/` endpoint.
export function registerIdentifyTool(server: McpServer): void { createPredictTool( server, "brickognize_identify", "Identify LEGO Item", "Identify any LEGO item (part, set, minifigure, or sticker) from a photograph. " + "Use this when the item type is unknown or the image may contain multiple types.\n\n" + "Provide imagePath — absolute path to a local image file (JPEG, PNG, or WebP).\n" + "Returns top matches with confidence scores, IDs, names, categories, and links to BrickLink/BrickOwl.", "/predict/", ); } - src/tools/predict.ts:22-51 (handler)The handler for the tool (within `createPredictTool`) processes the input image, calls the Brickognize API using the `predict` function, and maps the result.
async (input) => { try { const { blob, filename } = await resolveImage(input); const raw = await predict(endpoint, blob, filename); const result = mapPredictionResult(raw, input.includeRaw ?? false); return { content: [ { type: "text" as const, text: result.summary, }, { type: "text" as const, text: JSON.stringify(result, null, 2), }, ], }; } catch (error) { return { isError: true, content: [ { type: "text" as const, text: formatToolError(error), }, ], }; } }, - src/brickognize/client.ts:24-50 (helper)The actual network request to the Brickognize API is performed by this function.
export async function predict( endpoint: string, imageBlob: Blob, filename: string, ): Promise<RawSearchResults> { const form = new FormData(); form.append("query_image", imageBlob, filename); const res = await fetch(`${BASE_URL}${endpoint}`, { method: "POST", body: form, signal: AbortSignal.timeout(60_000), }); if (!res.ok) { const body = await res.text(); throw apiError(res.status, body); } const data = await res.json(); if (!data || typeof data.listing_id !== "string" || !Array.isArray(data.items)) { throw unexpectedResponse("missing listing_id or items array"); } return data as RawSearchResults; }