# Google Knowledge Panel Scraper (`searchapi/google-knowledge-panel-scraper`) Actor

Extracts public entity names, descriptions, structured attributes, websites, images, social profiles, and related entities from Google Knowledge Panels.

- **URL**: https://apify.com/searchapi/google-knowledge-panel-scraper.md
- **Developed by:** [Search API](https://apify.com/searchapi) (community)
- **Categories:** Developer tools, SEO tools, Other
- **Stats:** 2 total users, 1 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per usage

This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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 Knowledge Panel Scraper

Extracts public entity names, descriptions, structured attributes, websites, images, social profiles, and related entities from Google Knowledge Panels.

### What this Actor collects

The Actor converts Google Knowledge Panels into clean entity records containing the public name, description, structured attributes, website, images, social profiles, related entities, locale, and retrieval provenance when available.

- Uses the input limits and filters below to control the crawl.
- Stores source-backed fields defined by the 24-field dataset schema.
- Omits optional fields when the source does not expose a value instead of writing nulls or fabricated placeholders.

### Use cases

- Entity research
- Search-result verification
- Knowledge-graph enrichment

### Input

Provide input in JSON. Fields marked required must be supplied. The Default / example column shows a schema default when one exists; otherwise it shows a documented prefill or fixture value.

| Field | Type | Required | Default / example | Description |
| --- | --- | :---: | --- | --- |
| `query` | string | Yes | `"Albert Einstein"` | The entity name to look up (e.g. 'Albert Einstein', 'Eiffel Tower', 'Microsoft') |
| `gl` | string | No | `"us"` | Two-letter country code (e.g. 'us', 'uk', 'in') |
| `hl` | string | No | `"en"` | Two-letter language code (e.g. 'en', 'es', 'de') |
| `proxyConfiguration` | object | No | `{"useApifyProxy":true,"apifyProxyGroups":["GOOGLE_SERP"]}` | Proxy settings for the scraper. |

#### Example input

```json
{
  "query": "Albert Einstein",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "RESIDENTIAL"
    ],
    "countryCode": "US"
  },
  "gl": "us",
  "hl": "en"
}
```

### Output

The default dataset contains one item per extracted Knowledge Panel entity. The following are the most useful fields; attributes, social profiles, images, and related entities vary by panel type.

| Field | Type | Description |
| --- | --- | --- |
| `entityName` | string | Entity Name |
| `description` | string | Description |
| `entityType` | string | Entity Type |
| `website` | string | Website |
| `subtitle` | string | Subtitle |
| `searchQuery` | string | Search Query |
| `scrapedAt` | string | Scraped At |
| `type` | string | Type |
| `entityId` | string | Entity ID |
| `entityUrl` | string | Entity URL |
| `attributes` | object | Attributes |
| `imageUrl` | string | Image URL |
| `officialWebsite` | string | Official Website |
| `wikipediaUrl` | string | Wikipedia URL |
| `coordinates` | object | Coordinates |
| `aliases` | array | Aliases |

<details>
<summary>All 24 declared dataset fields</summary>

`entityName`, `entityId`, `entityUrl`, `description`, `attributes`, `website`, `imageUrl`, `officialWebsite`, `wikipediaUrl`, `coordinates`
`aliases`, `socialProfiles`, `relatedEntities`, `sourceUrls`, `entityType`, `subtitle`, `searchQuery`, `scrapedAt`, `type`, `resultType`
`searchUrl`, `searchMetadata`, `locale`, `retrieval`

</details>

#### Example dataset item

No static output record is embedded because the current local storage has no trustworthy item. Run the Actor with the example input to create source-backed output; the Actor does not fabricate a sample record.

### Related Actors

- [Google About This Result Scraper](https://apify.com/searchapi/google-about-this-result-scraper)
- [Google AI Overview Scraper](https://apify.com/searchapi/google-ai-overview-scraper)
- [Google Autocomplete Scraper](https://apify.com/searchapi/google-autocomplete-scraper)

# Actor input Schema

## `query` (type: `string`):

The entity name to look up (e.g. 'Albert Einstein', 'Eiffel Tower', 'Microsoft')

## `gl` (type: `string`):

Two-letter country code (e.g. 'us', 'uk', 'in')

## `hl` (type: `string`):

Two-letter language code (e.g. 'en', 'es', 'de')

## `proxyConfiguration` (type: `object`):

Proxy settings for the scraper.

## Actor input object example

```json
{
  "query": "Albert Einstein",
  "gl": "us",
  "hl": "en",
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": [
      "GOOGLE_SERP"
    ]
  }
}
```

# Actor output Schema

## `results` (type: `string`):

Schema for Google Knowledge Panel entity data.

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "query": "Albert Einstein",
    "gl": "us",
    "hl": "en"
};

// Run the Actor and wait for it to finish
const run = await client.actor("searchapi/google-knowledge-panel-scraper").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "query": "Albert Einstein",
    "gl": "us",
    "hl": "en",
}

# Run the Actor and wait for it to finish
run = client.actor("searchapi/google-knowledge-panel-scraper").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": "Albert Einstein",
  "gl": "us",
  "hl": "en"
}' |
apify call searchapi/google-knowledge-panel-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=searchapi/google-knowledge-panel-scraper",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/vqkbu6yInFmlOvB9M/builds/rEvLyjC9xPTQwWg3u/openapi.json