# AI Glasses Specs & Prices API (`star_dust/ai-glasses-specs-api`) Actor Structured, source-verified specs and fresh prices for every AI/smart-glasses device on the market — list, full specs, side-by-side compare, live price refresh. Built for AI agents (MCP-ready) and humans (CSV/JSON). - **URL**: https://apify.com/star\_dust/ai-glasses-specs-api.md - **Developed by:** [Star Dust](https://apify.com/star_dust) (community) - **Categories:** AI - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 device records This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## AI Glasses Specs & Prices API **Clean, current, structured data on every AI and smart-glasses device on the market — without scraping 15 manufacturer sites yourself.** The AI-glasses category is moving fast: new SKUs every quarter, silent price cuts, quiet discontinuations. This Actor maintains a curated, source-verified device database and re-checks prices live against official product pages. Built for **AI agents first** (MCP-ready, clean JSON) and humans second (CSV/dataset download). ### What you get Every device record carries: brand, model, release date, USD/EUR price, availability, display specs (type, resolution, field of view, brightness), weight, battery, audio, camera, **AI features** (assistant, live translation, visual AI — the fields generic spec sites don't structure), connectivity, prescription support, companion app, official URL, `updated_at`, and per-field `sources` — every value verified against a cited page or explicitly `null`. No fabricated specs. Coverage: Ray-Ban Meta (all gens), Meta Ray-Ban Display, Even Realities G1/G2, Xreal One series, Viture, Rokid, Snap Spectacles, Brilliant Labs Frame/Halo, TCL RayNeo, Amazon Echo Frames, Solos, Vuzix — and new Apple/Google entries the moment they ship. ### Modes | mode | what it does | |---|---| | `list` | One row per device: brand, model, price, availability, core flags | | `specs` | Full structured record for one device — fuzzy name match (`"ray-ban display"` works) | | `compare` | Field-by-field diff of two devices, `same` flag per row | | `dump` | The entire dataset, every field, with sources | | `refresh` | Live price + availability re-check against official pages, headless browser for bot-walled shops, sanity guards against bogus prices | #### Example input ```json { "mode": "compare", "device_a": "xreal one pro", "device_b": "viture luma pro" } ```` #### Example output (compare, excerpt) ```json { "field": "display.fov_deg", "xreal-one-pro": 57, "viture-luma-pro": 52, "same": false } { "field": "display.brightness_nits", "xreal-one-pro": 700, "viture-luma-pro": 1000, "same": false } ``` ### For AI agents (MCP) Add this Actor as a tool via the [Apify MCP server](https://mcp.apify.com) and your agent can answer "which AI glasses under $500 have live translation?" or "compare the Xreal One Pro and Viture Luma Pro" with verified, dated data instead of hallucinated specs. Results land in the `OUTPUT` key-value record as a single JSON object, and in the dataset for tabular export. ### Data honesty rules - Every field is verified from a fetched source, or `null`. Never guessed. - `field_sources` maps key fields to the exact URL they came from. - Price refresh rejects implausible scraped prices (bundle pages, accessory hits) instead of silently corrupting records. - Delisted product pages are flagged (`page-gone`) — supersession is data too. ### Pricing Pay-per-event: you pay a small fee per device record / compare / refresh run. No subscription. # Actor input Schema ## `mode` (type: `string`): What to do. `list` = one row per known device with brand, model, price, availability. `specs` = the full structured record for one device (needs `device`). `compare` = field-by-field diff of two devices (needs `device_a` + `device_b`). `dump` = the entire dataset with every field and per-field sources. `refresh` = re-check current price + availability against official product pages right now (uses a headless browser for bot-walled shops) and return the freshened dataset. ## `device` (type: `string`): Device name for `specs` mode. Fuzzy matched — 'ray-ban display', 'xreal one pro' or an exact id like 'even-realities-g1' all work. ## `device_a` (type: `string`): First device for `compare` mode (fuzzy matched). ## `device_b` (type: `string`): Second device for `compare` mode (fuzzy matched). ## `refresh_use_browser` (type: `boolean`): In `refresh` mode, retry bot-blocked or JavaScript-walled shop pages with a real headless browser. Slower but reaches Meta, Amazon, Snap and similar storefronts. ## Actor input object example ```json { "mode": "list", "device": "ray-ban meta gen 2", "device_a": "xreal one pro", "device_b": "viture luma pro", "refresh_use_browser": true } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "device": "ray-ban meta gen 2", "device_a": "xreal one pro", "device_b": "viture luma pro" }; // Run the Actor and wait for it to finish const run = await client.actor("star_dust/ai-glasses-specs-api").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "device": "ray-ban meta gen 2", "device_a": "xreal one pro", "device_b": "viture luma pro", } # Run the Actor and wait for it to finish run = client.actor("star_dust/ai-glasses-specs-api").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "device": "ray-ban meta gen 2", "device_a": "xreal one pro", "device_b": "viture luma pro" }' | apify call star_dust/ai-glasses-specs-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=star_dust/ai-glasses-specs-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Glasses Specs & Prices API", "description": "Structured, source-verified specs and fresh prices for every AI/smart-glasses device on the market — list, full specs, side-by-side compare, live price refresh. Built for AI agents (MCP-ready) and humans (CSV/JSON).", "version": "0.1", "x-build-id": "7ERJwSHp6AYEpOoWE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/star_dust~ai-glasses-specs-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-star_dust-ai-glasses-specs-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/star_dust~ai-glasses-specs-api/runs": { "post": { "operationId": "runs-sync-star_dust-ai-glasses-specs-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/star_dust~ai-glasses-specs-api/run-sync": { "post": { "operationId": "run-sync-star_dust-ai-glasses-specs-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "mode" ], "properties": { "mode": { "title": "Mode", "enum": [ "list", "specs", "compare", "dump", "refresh" ], "type": "string", "description": "What to do. `list` = one row per known device with brand, model, price, availability. `specs` = the full structured record for one device (needs `device`). `compare` = field-by-field diff of two devices (needs `device_a` + `device_b`). `dump` = the entire dataset with every field and per-field sources. `refresh` = re-check current price + availability against official product pages right now (uses a headless browser for bot-walled shops) and return the freshened dataset.", "default": "list" }, "device": { "title": "Device (specs mode)", "type": "string", "description": "Device name for `specs` mode. Fuzzy matched — 'ray-ban display', 'xreal one pro' or an exact id like 'even-realities-g1' all work." }, "device_a": { "title": "Device A (compare mode)", "type": "string", "description": "First device for `compare` mode (fuzzy matched)." }, "device_b": { "title": "Device B (compare mode)", "type": "string", "description": "Second device for `compare` mode (fuzzy matched)." }, "refresh_use_browser": { "title": "Use headless browser for walled pages (refresh mode)", "type": "boolean", "description": "In `refresh` mode, retry bot-blocked or JavaScript-walled shop pages with a real headless browser. Slower but reaches Meta, Amazon, Snap and similar storefronts.", "default": true } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```