# Google Immersive Product API | Product Pages for E-Commerce (`johnvc/google-immersive-product-api`) Actor Get Google's rich immersive product pages for any product search as structured JSON: title, brand, price range, aggregated rating and review breakdown, specs, variants, stores, videos, and user reviews. For e-commerce competitive intelligence and product research agents. Pay per product, MCP-ready. - **URL**: https://apify.com/johnvc/google-immersive-product-api.md - **Developed by:** [John](https://apify.com/johnvc) (community) - **Categories:** E-commerce, AI, SEO tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.00001 / actor start 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.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.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/platform/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 ## Google Immersive Product API | Rich Product Pages for E-Commerce Agents Get Google's rich immersive product pages for any product search as clean structured JSON. Give the API a product query and get back the deep product detail page Google shows shoppers, for the top matching products: title, brand, price range across stores, the aggregated rating and full star-by-star review breakdown, specs, variants, the stores selling it, related videos, and sample user reviews. It is the structured version of the page your customers and competitors are looking at. ### What you get One row per product: - `title`, `brand`, and `price_range` across stores - `rating` and `reviews` count, plus a `ratings` star-by-star breakdown - `about_the_product` specs, `variants`, and `thumbnails` - `stores` selling the product, related `videos`, and `user_reviews` ### Use cases - Pull the full product page for e-commerce competitive intelligence - Track a product's price range, rating, and review count over time - Compare variants and specs across competing products - Feed an AI shopping agent the rich product detail in one call - Build product-research datasets with specs, ratings, and store coverage ### Input | Field | Type | Description | |-------|------|-------------| | `query` | string | A single product search, e.g. `running shoes`. Provide this, `queries`, or both. | | `queries` | array of strings | A batch of product searches to run in one go. Merged with `query` and de-duplicated. | | `gl` | string | Optional two-letter country code for pricing and localization. Default `us`. | | `hl` | string | Optional two-letter language code. Default `en`. | | `maxResultsPerQuery` | integer | Products per query to pull the rich page for. Default 10, maximum 20. | #### Example input ```json { "query": "running shoes", "gl": "us", "maxResultsPerQuery": 10 } ```` ### Sample output ```json { "result_type": "product", "query": "running shoes", "position": 1, "title": "Adidas Men's Adizero Evo SL", "brand": "adidas", "price_range": "$150-$150", "rating": 4.8, "reviews": 19093, "ratings": [ { "stars": 5, "amount": 16553 }, { "stars": 4, "amount": 1507 } ], "about_the_product": { "...": "..." }, "variants": [ { "...": "..." } ], "stores": [ { "...": "..." } ], "thumbnails": [ "https://..." ] } ``` ### Pricing Pay-per-result: a small **$0.005 per-query search fee** (the lookup that finds the matching products) plus **$0.015 per product** page returned. Each product is a deep detail page, richer than a standard product listing, so a typical query is the price of one search plus the products it returns. ### How to get started 1. Open [Google Immersive Product API on the Apify Store](https://apify.com/johnvc/google-immersive-product-api?fpr=9n7kx3). 2. Enter a `query` (or a `queries` list of product searches). 3. Set `maxResultsPerQuery`, then run the Actor. 4. Export the dataset as JSON, CSV, or Excel, or pull it from the API. Prefer code? See [johnvc's GitHub for setup guides and code examples](https://github.com/johnisanerd/ApifyPublicData). ### Run from the API ```bash curl -X POST "https://api.apify.com/v2/acts/johnvc~google-immersive-product-api/run-sync-get-dataset-items?token=YOUR_APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"query":"running shoes","maxResultsPerQuery":5}' ``` ### 🔌 Use this API from Claude (MCP) This Actor is compatible with the Model Context Protocol (MCP), so AI agents can call it as a tool. Add it through the hosted Apify MCP server using this Actor-specific URL: https://mcp.apify.com/?tools=actors,docs,johnvc/google-immersive-product-api If you run agents from [Claude Code](https://claude.ai/referral/uIlpa7nPLg) (free trial) or [Claude Cowork](https://claude.ai/referral/uIlpa7nPLg) (free trial), add the Apify MCP server and ask it to "pull the rich product pages for the top 10 running shoes and compare ratings." Setup walkthrough: https://www.youtube.com/watch?v=jREWahDGhJM Apify MCP integration docs: https://docs.apify.com/platform/integrations/mcp #### MCP setup, step by step Visual setup guides for each client (source and more assets: [ApifyPublicData on GitHub](https://github.com/johnisanerd/ApifyPublicData)): **[Claude Cowork Desktop](https://claude.ai/referral/uIlpa7nPLg)** (free trial) ![Apify MCP install screenshot for the Cowork desktop app](https://raw.githubusercontent.com/johnisanerd/ApifyPublicData/main/assets/guides/install_mcp_into_claude_desktop.png) **[Claude Code](https://claude.ai/referral/uIlpa7nPLg)** (free trial) ![Apify MCP install screenshot for the Code CLI](https://raw.githubusercontent.com/johnisanerd/ApifyPublicData/main/assets/guides/install_mcp_into_claude_code.png) **Claude (website)** ![Install in Claude website](https://raw.githubusercontent.com/johnisanerd/ApifyPublicData/main/assets/guides/install_mcp_into_claude_ai.png) **Cursor** ![Install in Cursor](https://raw.githubusercontent.com/johnisanerd/ApifyPublicData/main/assets/guides/install_mcp_into_cursor.png) **ChatGPT** ![Install in ChatGPT](https://raw.githubusercontent.com/johnisanerd/ApifyPublicData/main/assets/guides/install_mcp_into_ChatGPT.png) ### FAQ **What is an immersive product page?** It is the rich product detail panel Google shows for a product, with specs, ratings, variants, stores, and reviews. This API returns that panel as structured data. **How does it find products?** It runs a shopping search for your query, then pulls the immersive page for the top matching products, up to `maxResultsPerQuery`. **How many products come back?** Up to `maxResultsPerQuery` (default 10) per query. **Can I research many products at once?** Yes. Pass a `queries` list; each search is run independently and its products are tagged with the source query. ### n8n integration Available as an n8n community node, **[n8n-nodes-google-immersive-product-api](https://www.npmjs.com/package/n8n-nodes-google-immersive-product-api)**. In n8n: Settings, Community Nodes, install `n8n-nodes-google-immersive-product-api`, then use it in any workflow (it also works as an AI Agent tool). ### Featured Tasks Ready-to-run examples that show this API solving a specific problem. Each opens its own setup so you can run it on your account in one click. - [Get Rich Product Detail Pages From a Google Search](https://apify.com/johnvc/google-immersive-product-api/examples/get-rich-product-detail-pages-from-a-google-search?fpr=9n7kx3) - [Get a Product's Ratings and Reviews From Google](https://apify.com/johnvc/google-immersive-product-api/examples/get-a-product-s-ratings-and-reviews-from-google?fpr=9n7kx3) - [Get Apple Watch Prices and Ratings as JSON](https://apify.com/johnvc/google-immersive-product-api/examples/get-apple-watch-prices-and-ratings-as-json?fpr=9n7kx3) - [Get Laptop Prices, Brands, and Ratings as JSON](https://apify.com/johnvc/google-immersive-product-api/examples/get-laptop-prices-brands-and-ratings-as-json?fpr=9n7kx3) Last Updated: 2026.06.17 # Actor input Schema ## `query` (type: `string`): Enter a single product search, for example 'running shoes' or 'wireless earbuds'. Provide this, `queries`, or both. The Actor returns the rich immersive product page for the top matching products. ## `queries` (type: `array`): Provide a list of product searches to run in one batch. Merged with `query` and de-duplicated. ## `gl` (type: `string`): Set the two-letter country code for pricing and localization (e.g. 'us', 'gb', 'de'). Defaults to 'us'. ## `hl` (type: `string`): Set the two-letter interface language code (e.g. 'en', 'es', 'de'). Defaults to 'en'. ## `maxResultsPerQuery` (type: `integer`): How many products to return the rich immersive page for, per query. Default 10, maximum 20. ## Actor input object example ```json { "query": "running shoes", "gl": "us", "hl": "en", "maxResultsPerQuery": 10 } ``` # Actor output Schema ## `results` (type: `string`): All product rows stored in the default dataset, one item per product. # 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 = { "query": "running shoes", "gl": "us", "hl": "en" }; // Run the Actor and wait for it to finish const run = await client.actor("johnvc/google-immersive-product-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 = { "query": "running shoes", "gl": "us", "hl": "en", } # Run the Actor and wait for it to finish run = client.actor("johnvc/google-immersive-product-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 '{ "query": "running shoes", "gl": "us", "hl": "en" }' | apify call johnvc/google-immersive-product-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=johnvc/google-immersive-product-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Google Immersive Product API | Product Pages for E-Commerce", "description": "Get Google's rich immersive product pages for any product search as structured JSON: title, brand, price range, aggregated rating and review breakdown, specs, variants, stores, videos, and user reviews. For e-commerce competitive intelligence and product research agents. Pay per product, MCP-ready.", "version": "0.0", "x-build-id": "5iil8yuGITWaPpWXM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/johnvc~google-immersive-product-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-johnvc-google-immersive-product-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/johnvc~google-immersive-product-api/runs": { "post": { "operationId": "runs-sync-johnvc-google-immersive-product-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/johnvc~google-immersive-product-api/run-sync": { "post": { "operationId": "run-sync-johnvc-google-immersive-product-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "query": { "title": "Product Query", "type": "string", "description": "Enter a single product search, for example 'running shoes' or 'wireless earbuds'. Provide this, `queries`, or both. The Actor returns the rich immersive product page for the top matching products." }, "queries": { "title": "Product Queries", "type": "array", "description": "Provide a list of product searches to run in one batch. Merged with `query` and de-duplicated.", "items": { "type": "string" } }, "gl": { "title": "Country Code", "type": "string", "description": "Set the two-letter country code for pricing and localization (e.g. 'us', 'gb', 'de'). Defaults to 'us'.", "default": "us" }, "hl": { "title": "Language Code", "type": "string", "description": "Set the two-letter interface language code (e.g. 'en', 'es', 'de'). Defaults to 'en'.", "default": "en" }, "maxResultsPerQuery": { "title": "Maximum Products Per Query", "minimum": 1, "maximum": 20, "type": "integer", "description": "How many products to return the rich immersive page for, per query. Default 10, maximum 20.", "default": 10 } } }, "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 } } } } } } } } } } ```