# 🔍 Google Scholar Scraper (`scrapium/google-scholar-scraper`) Actor

- **URL**: https://apify.com/scrapium/google-scholar-scraper.md
- **Developed by:** [Scrapium](https://apify.com/scrapium) (community)
- **Categories:** Automation, Lead generation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet

## Pricing

from $3.99 / 1,000 results

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.

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 Scholar Scraper

A blazing-fast, **production-grade** Apify Actor that pulls academic papers from the global Scholar knowledge graph (OpenAlex + Semantic Scholar) and delivers clean, structured JSON ready for analysis, citation review, or literature dashboards.

> **Bulk in. Citations out.** Throw a list of keywords or Google Scholar URLs and walk away — the Actor does the heavy lifting.

---

### 🚀 Why Choose This Actor?

* 🧠 **Multi-source intelligence** — combines OpenAlex (250 M+ works) **and** Semantic Scholar so you never miss a paper.
* 🌐 **Smart auto-escalating proxy** — starts direct, falls back to **Datacenter → Residential** only when needed. You don't have to think about it.
* ⚡ **Live streaming results** — each paper hits the dataset the moment it's scraped. A crash mid-run still leaves you with rows.
* 🧹 **Built-in deduplication, filters, and sort** — citations, recency, open-access, article-type filters out of the box.
* 🪶 **Light & fast** — no headless browser, no Playwright overhead — just well-engineered HTTP calls.
* 💸 **Pay only for what you use** — no hidden compute time waste.

---

### ✨ Key Features

* 🔎 **Bulk search** — submit dozens of queries / Scholar URLs at once.
* 📥 **Up to 5 000 papers per query** with cursor-based pagination.
* 🏷️ **Rich metadata** — title, authors, year, citations, source, PDF link, abstract snippet, etc.
* 🛡️ **Auto-rotating proxies** with sticky residential mode after escalation.
* 📊 **Two pre-configured dataset views** — Overview (essentials) + Full Details (everything).
* 📝 **Per-query sectioning** — every record carries a `query` field so you can split results by topic in seconds.

---

### ⚙️ Input

| Field | Type | Description |
|-------|------|-------------|
| `searchQueries` ✱ | array of strings | Search keywords **or** Scholar URLs (e.g. `https://scholar.google.com/scholar?q=...`). Required. |
| `maxItems` | integer (1 – 5000) | Max papers per query. Default `100`. |
| `sortBy` | enum | `relevance` *(default)* \| `cited_by_count` |
| `filter` | enum | `all` *(default)* \| `has_pdf` \| `open_access` \| `recent_5_years` |
| `articleType` | enum | `any` *(default)* \| `journal` \| `conference` \| `book` \| `preprint` |
| `proxyConfiguration` | object | Optional. Defaults to **no proxy** — the actor will auto-escalate to Datacenter/Residential on rate-limits. |

#### Example input

```json
{
  "searchQueries": [
    "Tomato Shelf Life Prediction using IoT and Machine Learning",
    "Federated learning healthcare"
  ],
  "maxItems": 100,
  "sortBy": "cited_by_count",
  "filter": "open_access",
  "articleType": "journal",
  "proxyConfiguration": { "useApifyProxy": false }
}
````

***

### 📦 Output

Each dataset row matches the well-known **Scholar / SerpAPI-style** shape:

```json
{
  "query": "Tomato Shelf Life Prediction using IoT and Machine Learning",
  "cidCode": "W4409060190",
  "didCode": "W4409060190",
  "lidCode": "",
  "aidCode": "W4409060190",
  "resultIndex": 0,
  "type": "ARTICLE",
  "title": "Tomato Shelf Life Prediction using IoT and Machine Learning",
  "link": "https://doi.org/10.1109/iciset62123.2024.10939467",
  "documentLink": "",
  "documentType": "",
  "fullAttribution": "Nazmul Arafin Naim, Raisul Islam, Mohammed Saifuddin, ... - , 2024",
  "authors": "Nazmul Arafin Naim, Raisul Islam, Mohammed Saifuddin, ...",
  "publication": "",
  "year": 2024,
  "source": "",
  "searchMatch": "Predicting tomato shelf life is crucial for ...",
  "citations": 1,
  "citationsLink": "https://openalex.org/W4409060190",
  "relatedArticlesLink": "https://openalex.org/W4409060190",
  "versions": 1,
  "versionsLink": "https://openalex.org/W4409060190"
}
```

| Field | Meaning |
|-------|---------|
| `query` | Original query that produced this row (lets you group sections). |
| `cidCode` / `didCode` / `aidCode` | Stable record identifiers (OpenAlex ID or hash). |
| `resultIndex` | Position within that query's result set. |
| `title` | Paper title. |
| `authors` | Up to five lead authors. |
| `publication` / `source` | Journal / venue name. |
| `year` | Publication year. |
| `citations` | Total citation count. |
| `documentLink` / `documentType` | Direct PDF/OA URL when available. |
| `searchMatch` | Abstract snippet (first ~300 chars). |
| `citationsLink` / `relatedArticlesLink` / `versionsLink` | Apify-friendly clickable links. |

***

### 🚀 How to Use (Apify Console)

1. Log in at <https://console.apify.com> → **Actors**.
2. Open **Google Scholar Scraper**.
3. Paste your queries (or Scholar URLs) into **Search Queries**.
4. Tune `maxItems`, `sortBy`, `filter`, `articleType` to taste.
5. Leave **Proxy** on its default (no proxy) — the Actor auto-escalates on rate-limits.
6. Click **▶ Start**.
7. Watch the live log — every section reports progress in real time.
8. Open the **Output** tab and export to JSON / CSV / XLSX.

### 🤖 Use via API

```bash
curl -X POST "https://api.apify.com/v2/acts/<ACTOR_ID>/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
     -H "Content-Type: application/json" \
     -d '{
       "searchQueries": ["Federated learning healthcare"],
       "maxItems": 50,
       "sortBy": "cited_by_count"
     }'
```

***

### 🎯 Best Use Cases

- 🔬 **Literature reviews** — pull a full corpus on a research topic in minutes.
- 📈 **Citation tracking** — monitor how a paper or author cluster grows over time.
- 🧪 **Trend detection** — slice by `recent_5_years` to spot emerging directions.
- 📚 **Library / EdTech tools** — feed clean, normalised records into your platform.
- 🤖 **AI agents** — give RAG/LLM pipelines high-quality academic context.

***

### 💸 Pricing

This Actor is best deployed under the **Pay-per-event (PPE)** model:

- One event = one paper pushed to the dataset (`apify-default-dataset-item`).
- No surprise compute charges, no rental — you pay for results, not waiting.
- Free **5-second startup** included by Apify on every run.

> Configure the exact event prices in the Apify Console → **Publication → Monetization** tab.

***

### ❓ Frequently Asked Questions

**Q: Do I need a Google Scholar account?**
No. We connect to OpenAlex + Semantic Scholar — both are open scholarly knowledge graphs.

**Q: How fresh is the data?**
OpenAlex syncs daily with Crossref, DOAJ, PubMed and others. Most papers appear within 24 – 48 h of publication.

**Q: Will I get blocked?**
Unlikely — the actor uses official, rate-limit-friendly APIs and auto-escalates through Datacenter → Residential proxies if a host ever pushes back.

**Q: Can I pass full Scholar URLs instead of keywords?**
Yes. URLs like `https://scholar.google.com/scholar?q=...` are auto-parsed for the `q=` term.

**Q: Why two views in the output?**
The **Overview** view is great for quick scanning. The **Full Details** view is the complete record — same data, more columns.

***

### 🛟 Support & Feedback

Found a bug or have a feature request? Open an issue or message us through the Apify Store page. We respond fast.

***

### ⚖️ Cautions / Legal

- Data is collected only from **publicly available sources** (OpenAlex, Semantic Scholar).
- You are responsible for downstream use that complies with GDPR/CCPA, target ToS, and copyright.
- Respect rate-limits and `robots.txt` — being a good citizen reduces blocks too.

# Actor input Schema

## `searchQueries` (type: `array`):

Bulk list of search keywords (e.g. "Tomato Shelf Life Prediction") OR full Google Scholar URLs (e.g. https://scholar.google.com/scholar?q=...). One per line. Required.

## `maxItems` (type: `integer`):

Maximum number of papers to fetch per query.

## `filter` (type: `string`):

Restrict results by availability or recency.

## `newerThan` (type: `integer`):

Scrape only articles from this year on. Effective only when not sorting by date. Example: 2020 keeps everything published in 2020 or later.

## `olderThan` (type: `integer`):

Scrape articles up to this year. Effective only when not sorting by date. Example: 2024 keeps everything published in 2024 or earlier.

## `sortBy` (type: `string`):

How to order the final results.

## `articleType` (type: `string`):

Restrict to a specific article type.

## `enableDebugDumps` (type: `boolean`):

Store a dump of every API response (OpenAlex + Semantic Scholar) into the default key-value store so you can inspect what was fetched. Useful for troubleshooting.

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

By default the actor connects directly. If a request is blocked or rate-limited, it auto-escalates to a Datacenter proxy, then to a Residential proxy (with 3 retries). Once switched to Residential, that stays sticky for the rest of the run.

## Actor input object example

```json
{
  "searchQueries": [
    "Tomato Shelf Life Prediction using IoT and Machine Learning"
  ],
  "maxItems": 10,
  "filter": "all",
  "sortBy": "relevance",
  "articleType": "any",
  "enableDebugDumps": false,
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}
```

# 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 = {
    "searchQueries": [
        "Tomato Shelf Life Prediction using IoT and Machine Learning"
    ],
    "proxyConfiguration": {
        "useApifyProxy": false
    }
};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapium/google-scholar-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 = {
    "searchQueries": ["Tomato Shelf Life Prediction using IoT and Machine Learning"],
    "proxyConfiguration": { "useApifyProxy": False },
}

# Run the Actor and wait for it to finish
run = client.actor("scrapium/google-scholar-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 '{
  "searchQueries": [
    "Tomato Shelf Life Prediction using IoT and Machine Learning"
  ],
  "proxyConfiguration": {
    "useApifyProxy": false
  }
}' |
apify call scrapium/google-scholar-scraper --silent --output-dataset

```

## MCP server setup

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

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "🔍 Google Scholar Scraper",
        "description": null,
        "version": "0.2",
        "x-build-id": "YlK3cCUoJv3sIZd4T"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/scrapium~google-scholar-scraper/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-scrapium-google-scholar-scraper",
                "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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/scrapium~google-scholar-scraper/runs": {
            "post": {
                "operationId": "runs-sync-scrapium-google-scholar-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/scrapium~google-scholar-scraper/run-sync": {
            "post": {
                "operationId": "run-sync-scrapium-google-scholar-scraper",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": [
                    "searchQueries"
                ],
                "properties": {
                    "searchQueries": {
                        "title": "🔎 Search Queries / Scholar URLs",
                        "type": "array",
                        "description": "Bulk list of search keywords (e.g. \"Tomato Shelf Life Prediction\") OR full Google Scholar URLs (e.g. https://scholar.google.com/scholar?q=...). One per line. Required.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "maxItems": {
                        "title": "📊 Max items per query",
                        "minimum": 1,
                        "maximum": 10000,
                        "type": "integer",
                        "description": "Maximum number of papers to fetch per query.",
                        "default": 10
                    },
                    "filter": {
                        "title": "🧰 Result filter",
                        "enum": [
                            "all",
                            "has_pdf",
                            "open_access",
                            "recent_5_years"
                        ],
                        "type": "string",
                        "description": "Restrict results by availability or recency.",
                        "default": "all"
                    },
                    "newerThan": {
                        "title": "🕐 Newer than (year)",
                        "minimum": 1800,
                        "maximum": 2100,
                        "type": "integer",
                        "description": "Scrape only articles from this year on. Effective only when not sorting by date. Example: 2020 keeps everything published in 2020 or later."
                    },
                    "olderThan": {
                        "title": "🕒 Older than (year)",
                        "minimum": 1800,
                        "maximum": 2100,
                        "type": "integer",
                        "description": "Scrape articles up to this year. Effective only when not sorting by date. Example: 2024 keeps everything published in 2024 or earlier."
                    },
                    "sortBy": {
                        "title": "🔃 Sort results by",
                        "enum": [
                            "relevance",
                            "cited_by_count"
                        ],
                        "type": "string",
                        "description": "How to order the final results.",
                        "default": "relevance"
                    },
                    "articleType": {
                        "title": "📑 Article type",
                        "enum": [
                            "any",
                            "journal",
                            "conference",
                            "book",
                            "preprint"
                        ],
                        "type": "string",
                        "description": "Restrict to a specific article type.",
                        "default": "any"
                    },
                    "enableDebugDumps": {
                        "title": "🐞 Enable debug dumps",
                        "type": "boolean",
                        "description": "Store a dump of every API response (OpenAlex + Semantic Scholar) into the default key-value store so you can inspect what was fetched. Useful for troubleshooting.",
                        "default": false
                    },
                    "proxyConfiguration": {
                        "title": "🌐 Proxy Configuration",
                        "type": "object",
                        "description": "By default the actor connects directly. If a request is blocked or rate-limited, it auto-escalates to a Datacenter proxy, then to a Residential proxy (with 3 retries). Once switched to Residential, that stays sticky for the rest of the run.",
                        "default": {
                            "useApifyProxy": false
                        }
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```