# Presearch AI Results Scraper (`searchapi/presearch-ai-results-scraper`) Actor

Scrapes Presearch PandaChat answers with cited sources, organic search context, related questions, and normalized metadata.

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

## Pricing

from $1.99 / 1,000 search 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/actors/running/actors-in-store.md#pay-per-event

## 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

## Presearch AI Results Scraper

This Actor submits one or more prompts to Presearch and extracts the PandaChat answer together with the public organic results that support it.

### Input

- `prompt` (required): the primary search prompt.
- `prompts`: optional additional prompts. Duplicates are removed.
- `maxItems`: maximum number of prompts to process, from 1 to 100.
- `maxRequestRetries`: bounded retries per prompt, from 0 to 5.
- `proxyConfiguration`: Apify Proxy or custom proxy configuration.

### Dataset records

Each successful prompt produces one normalized record containing a stable ID, prompt, answer text and available HTML, answer and word counts, citation indexes, cited source objects, all organic source objects, related questions, the Presearch result ID, provider, search URL, and scrape timestamp.

Each source can include its position, title, URL, domain, snippet, provider, and favicon URL. Unavailable fields are omitted rather than filled with placeholders.

The Actor listens for Presearch's public JSON and event-stream responses before navigation. It validates response status and content type, maps only documented dataset fields, and uses the rendered PandaChat card as a fallback when the summary response is unavailable. It never stores raw API payloads.

Presearch currently applies Cloudflare access controls to many datacenter and workstation IPs. Direct runs detect that response and fail closed. Use an authorized Residential proxy when permitted; the Actor does not attempt to solve or bypass interactive challenges. Proxy credentials are never read from environment variables or written to output.

If Presearch does not return a usable PandaChat answer after bounded retries, the run fails instead of publishing a citation-only or fabricated record.

### Local validation

```powershell
npm test
apify validate-schema
apify run --purge
```

# Actor input Schema

## `prompt` (type: `string`):

The prompt/query to search for AI-generated answers on Presearch

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

Maximum number of AI answers to retrieve

## `prompts` (type: `array`):

Optional additional prompts to run after the primary prompt. Duplicate prompts are removed.

## `maxRequestRetries` (type: `integer`):

Maximum retries per failed prompt.

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

Proxy configuration for the scraper

## Actor input object example

```json
{
  "prompt": "capital of France",
  "maxItems": 1,
  "prompts": [],
  "maxRequestRetries": 2,
  "proxyConfiguration": {
    "useApifyProxy": true
  }
}
```

# Actor output Schema

## `dataset` (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 = {
    "prompt": "capital of France",
    "maxItems": 1,
    "prompts": []
};

// Run the Actor and wait for it to finish
const run = await client.actor("searchapi/presearch-ai-results-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 = {
    "prompt": "capital of France",
    "maxItems": 1,
    "prompts": [],
}

# Run the Actor and wait for it to finish
run = client.actor("searchapi/presearch-ai-results-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "prompt": "capital of France",
  "maxItems": 1,
  "prompts": []
}' |
apify call searchapi/presearch-ai-results-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,searchapi/presearch-ai-results-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/awKnqzQRwjdyFBTf1/builds/PCb0I4LYwOp8Cpj6h/openapi.json