# Second Brain Builder — Karpathy's LLM Wiki, Automated (`openclawai/second-brain-builder`) Actor

Transform web content into an organized Obsidian-compatible knowledge base with AI-powered compilation. Scrapes any website and generates a Second Brain structure with wikilinks.

- **URL**: https://apify.com/openclawai/second-brain-builder.md
- **Developed by:** [Pika Choo](https://apify.com/openclawai) (community)
- **Categories:** AI, Agents, MCP servers
- **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 1 bookmarks
- **User rating**: No ratings yet

## Pricing

Pay per event

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

## Second Brain Builder — Karpathy's LLM Wiki, Automated

**The tool Andrej Karpathy described. Built and automated.**

Turn any URL, article, meeting note, or transcript into an organized Obsidian-compatible knowledge base — with AI-generated wikilinks, entity maps, concept clusters, and synthesis pages. Zero setup. No database. No config files.

Just sources in. Organized knowledge out.

---

### Why This Exists

Andrej Karpathy posted his personal LLM knowledge base workflow — a system where AI reads your sources and builds a navigable wiki of everything you've collected. The internet went wild.

This actor automates that exact system. Paste URLs or raw notes, click Start, get back a complete Second Brain structure ready to open in Obsidian or query with Claude.

---

### What You Get

````

your-vault/
├── raw/                    ← every source preserved with metadata
├── wiki/
│   ├── sources/            ← one AI summary per source
│   ├── entities/           ← people, companies, tools, products
│   ├── concepts/           ← ideas, frameworks, methods
│   ├── synthesis/          ← cross-source comparisons & analyses
│   ├── index.md            ← master catalog of everything
│   └── log.md              ← what the AI built and why
├── outputs/                ← your Q\&A and reports go here
├── CLAUDE.md               ← AI maintenance guide (add more sources later)
└── README.md               ← getting started

```

Open the folder as an Obsidian vault. Every page links to related pages with `[[wikilinks]]`. Navigate your knowledge like Wikipedia.

---

### How It Works

#### 1. Input Your Sources
Two methods — use either or both together:

**URLs** — paste any web pages: articles, blog posts, documentation, research papers
```

https://paulgraham.com/startupideas.html
https://karpathy.ai/blog/
https://docs.anthropic.com/en/docs/

````

**Raw Content** — paste text directly: meeting notes, transcripts, interview summaries, email threads
```json
{
  "title": "Team Meeting - April 8",
  "content": "We discussed Q2 priorities..."
}
````

Mix and match freely in the same run.

#### 2. AI Organizes Everything

Claude Sonnet 4.6 reads all your sources and extracts:

- **Entities** — people, companies, tools, products (proper nouns worth tracking)
- **Concepts** — ideas, frameworks, theories, methods (abstract knowledge)
- **Synthesis** — comparisons and analyses that span multiple sources

Every topic gets: a summary, key points, related topics with `[[wikilinks]]`, and source citations.

#### 3. Download Your Wiki

All files saved to Apify key-value store. Download as a folder or ZIP. Open in:

- **Obsidian** — browse wikilinks visually
- **VS Code** — `code .`
- **Claude Code** — `claude .` then ask anything

***

### Example Output

#### wiki/index.md

```markdown
## AI and Startups — Knowledge Base

### Entities (4)
- [[Paul Graham]] — Y Combinator founder, essay writer on startups...
- [[Andrej Karpathy]] — AI researcher, former Tesla/OpenAI...
- [[Y Combinator]] — Startup accelerator, batch model...
- [[OpenAI]] — AI research lab...

### Concepts (6)
- [[Startup Ideas]] — How to find problems worth solving...
- [[Product Market Fit]] — Achieving PMF strategies...
- [[AI Alignment]] — Ensuring AI systems behave as intended...
```

#### wiki/concepts/Startup-Ideas.md

```markdown
---
tags: [startups, ideas, founder-advice]
category: concept
created: 2026-04-08
sources: 3
---

## Startup Ideas

### Summary
The best startup ideas come from problems you personally experience...

### Key Points
- Work on problems you have yourself
- Start with a narrow target market
- Ideas that seem bad often become great companies

### Related Topics
- [[Founder Mindset]]
- [[Product Market Fit]]
- [[Paul Graham]]

### Sources
- [How to Get Startup Ideas — Paul Graham](https://paulgraham.com/startupideas.html)
- [Startup School Lecture 2024](https://...)
```

***

### Use Cases

**Personal Knowledge Management**
Research projects, learning new skills, building expertise in any domain.

**Business Intelligence**
Organize competitor research, industry news, market analysis into a queryable wiki.

**Content Creation**
Build research bases for newsletters, blogs, podcasts, video scripts.

**Academic Research**
Structure papers, sources, and notes for thesis work or literature reviews.

**Meeting Intelligence**
Paste transcripts and notes. Get back organized action items, decisions, and concept maps.

***

### Asking Questions After

Once your wiki is built, open it in Claude Code and ask:

```
"What are the main themes across all these sources?"
"What does source A say vs source B about [topic]?"
"Who are the key people in this knowledge base and what do they believe?"
"What gaps should I research next?"
"Write a 500-word briefing on [concept]"
```

The `CLAUDE.md` file tells your AI exactly how to maintain and extend the wiki.

***

### Pricing

Pay only when a knowledge base is successfully created:

| Knowledge Base Size | Topics Generated | Price |
|---------------------|-----------------|-------|
| Small | 1–5 topics | $0.50 |
| Medium | 6–15 topics | $1.50 |
| Large | 16–30 topics | $3.00 |
| Huge | 31+ topics | $5.00 |

No charges for failed runs. No hidden fees.

***

### Input Options

| Parameter | Type | Description |
|-----------|------|-------------|
| `urls` | array | Web pages to scrape |
| `rawContent` | array | Direct text input (title + content) |
| `topic` | string | What this knowledge base is about |
| `maxPages` | integer | Max sources to process (default: 50) |
| `includeScreenshots` | boolean | Save visual snapshots (default: false) |
| `useLightpanda` | boolean | 10x faster scraping for large batches |
| `useProfile` | boolean | Persistent browser profile for auth bypass |

***

### Tips for Best Results

**URL selection:**

- Use article pages and long-form content, not homepages
- Mix multiple authors and perspectives
- 10–50 sources gives the best AI organization

**Topic description:**

- Good: `"AI safety research and alignment strategies"`
- Good: `"B2B SaaS marketing and growth tactics for 2026"`
- Bad: `"stuff"` or `"everything"`

**Page limits:**

- 10–20 pages: quick test or narrow topic
- 50–100 pages: standard knowledge base
- 200–500 pages: comprehensive research

***

### FAQ

**What websites can I scrape?**
Almost any public website. Uses agent-browser (Vercel Labs) which handles JavaScript-heavy sites, SPAs, and dynamic content. Cannot access paywalled or login-protected content unless you enable persistent profile mode.

**Do I need an AI API key?**
No. AI is included. We handle the Vercel AI Gateway integration with Claude Sonnet 4.6.

**Is this compatible with Obsidian?**
100%. Proper YAML frontmatter, `[[wikilinks]]`, and markdown structure that Obsidian loves natively.

**Can I add more sources later?**
Yes. Drop new files into `raw/` and tell Claude: *"Read new files in raw/ and update wiki/ following CLAUDE.md rules."*

**How is this different from bookmarking?**
Bookmarks are unorganized lists. This gives you organized topics with summaries, connections between concepts, and a wiki that's immediately queryable by AI.

**What's the difference between Lightpanda mode and normal mode?**
Lightpanda is a purpose-built headless browser engine — 10x faster and 10x less memory than Chrome. Use it for large batches. Note: Lightpanda doesn't support persistent profiles.

***

### Credits

Inspired by Andrej Karpathy's personal LLM knowledge base system.

**Built by OpenClaw AI** — making AI-powered knowledge management accessible to everyone.

# Actor input Schema

## `urls` (type: `array`):

Paste your bookmarks, articles, docs - everything you want organized. We'll scrape them all and turn them into your personal wiki.

## `rawContent` (type: `array`):

Have meeting transcripts, lab results, email threads, or course notes? Paste them here as objects with 'title' and 'content'. Each becomes a source in your Second Brain.

## `topic` (type: `string`):

Name your Second Brain (e.g., 'AI & Startup Advice', 'Marketing Playbook', 'Developer Resources')

## `maxPages` (type: `integer`):

How many pages to scrape? Start with 10-50 for testing, scale to 1000s for production.

## `includeScreenshots` (type: `boolean`):

Capture visual snapshots of each page (useful for design refs, infographics, diagrams)

## `useLightpanda` (type: `boolean`):

10x faster scraping for large batches (100+ pages). Recommended for production runs.

## `useProfile` (type: `boolean`):

Bypass login screens and paywalls. Enable for sites behind authentication (Medium, Reddit, LinkedIn).

## `userPrompt` (type: `string`):

Optional instructions to guide how AI organizes your knowledge base. E.g. 'Focus on actionable advice only' or 'Write summaries as bullet points' or 'Treat this as competitor research, highlight weaknesses'.

## Actor input object example

```json
{
  "rawContent": [
    {
      "title": "Meeting Notes - Q1 Planning",
      "content": "# Key Takeaways\n- Launch new feature by March\n- Hire 2 engineers\n- Focus on enterprise customers"
    }
  ],
  "maxPages": 50,
  "includeScreenshots": false,
  "useLightpanda": false,
  "useProfile": false
}
```

# Actor output Schema

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

No description

# 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 = {
    "rawContent": [
        {
            "title": "Meeting Notes - Q1 Planning",
            "content": "# Key Takeaways\n- Launch new feature by March\n- Hire 2 engineers\n- Focus on enterprise customers"
        }
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("openclawai/second-brain-builder").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 = { "rawContent": [{
            "title": "Meeting Notes - Q1 Planning",
            "content": """# Key Takeaways
- Launch new feature by March
- Hire 2 engineers
- Focus on enterprise customers""",
        }] }

# Run the Actor and wait for it to finish
run = client.actor("openclawai/second-brain-builder").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 '{
  "rawContent": [
    {
      "title": "Meeting Notes - Q1 Planning",
      "content": "# Key Takeaways\\n- Launch new feature by March\\n- Hire 2 engineers\\n- Focus on enterprise customers"
    }
  ]
}' |
apify call openclawai/second-brain-builder --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=openclawai/second-brain-builder",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

```json
{
    "openapi": "3.0.1",
    "info": {
        "title": "Second Brain Builder — Karpathy's LLM Wiki, Automated",
        "description": "Transform web content into an organized Obsidian-compatible knowledge base with AI-powered compilation. Scrapes any website and generates a Second Brain structure with wikilinks.",
        "version": "1.0",
        "x-build-id": "fUn7y0ODz5EkHVh3g"
    },
    "servers": [
        {
            "url": "https://api.apify.com/v2"
        }
    ],
    "paths": {
        "/acts/openclawai~second-brain-builder/run-sync-get-dataset-items": {
            "post": {
                "operationId": "run-sync-get-dataset-items-openclawai-second-brain-builder",
                "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": {
                                "$ref": "#/components/schemas/inputSchema"
                            }
                        }
                    }
                },
                "parameters": [
                    {
                        "name": "token",
                        "in": "query",
                        "required": true,
                        "schema": {
                            "type": "string"
                        },
                        "description": "Enter your Apify token here"
                    }
                ],
                "responses": {
                    "200": {
                        "description": "OK"
                    }
                }
            }
        },
        "/acts/openclawai~second-brain-builder/runs": {
            "post": {
                "operationId": "runs-sync-openclawai-second-brain-builder",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor and returns information about the initiated run in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": {
                                    "$ref": "#/components/schemas/runsResponseSchema"
                                }
                            }
                        }
                    }
                }
            }
        },
        "/acts/openclawai~second-brain-builder/run-sync": {
            "post": {
                "operationId": "run-sync-openclawai-second-brain-builder",
                "x-openai-isConsequential": false,
                "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
                "tags": [
                    "Run Actor"
                ],
                "requestBody": {
                    "required": true,
                    "content": {
                        "application/json": {
                            "schema": {
                                "$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": [
                    "topic"
                ],
                "properties": {
                    "urls": {
                        "title": "📥 URLs to Scrape",
                        "type": "array",
                        "description": "Paste your bookmarks, articles, docs - everything you want organized. We'll scrape them all and turn them into your personal wiki.",
                        "items": {
                            "type": "string"
                        }
                    },
                    "rawContent": {
                        "title": "📝 Or Paste Raw Content Directly",
                        "type": "array",
                        "description": "Have meeting transcripts, lab results, email threads, or course notes? Paste them here as objects with 'title' and 'content'. Each becomes a source in your Second Brain.",
                        "items": {
                            "type": "object",
                            "properties": {
                                "title": {
                                    "type": "string",
                                    "title": "Title",
                                    "description": "Title of this content item",
                                    "editor": "textfield"
                                },
                                "content": {
                                    "type": "string",
                                    "title": "Content",
                                    "description": "Markdown or plain text content",
                                    "editor": "textarea"
                                }
                            },
                            "required": [
                                "title",
                                "content"
                            ]
                        }
                    },
                    "topic": {
                        "title": "🎯 What's This Knowledge Base About?",
                        "minLength": 3,
                        "type": "string",
                        "description": "Name your Second Brain (e.g., 'AI & Startup Advice', 'Marketing Playbook', 'Developer Resources')"
                    },
                    "maxPages": {
                        "title": "📊 Max Pages",
                        "minimum": 1,
                        "maximum": 1000,
                        "type": "integer",
                        "description": "How many pages to scrape? Start with 10-50 for testing, scale to 1000s for production.",
                        "default": 50
                    },
                    "includeScreenshots": {
                        "title": "📸 Save Screenshots",
                        "type": "boolean",
                        "description": "Capture visual snapshots of each page (useful for design refs, infographics, diagrams)",
                        "default": false
                    },
                    "useLightpanda": {
                        "title": "🚀 Fast Mode",
                        "type": "boolean",
                        "description": "10x faster scraping for large batches (100+ pages). Recommended for production runs.",
                        "default": false
                    },
                    "useProfile": {
                        "title": "🔐 Smart Authentication",
                        "type": "boolean",
                        "description": "Bypass login screens and paywalls. Enable for sites behind authentication (Medium, Reddit, LinkedIn).",
                        "default": false
                    },
                    "userPrompt": {
                        "title": "🎨 Custom AI Instructions",
                        "type": "string",
                        "description": "Optional instructions to guide how AI organizes your knowledge base. E.g. 'Focus on actionable advice only' or 'Write summaries as bullet points' or 'Treat this as competitor research, highlight weaknesses'."
                    }
                }
            },
            "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
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }
    }
}
```