# AI Web Search & RAG Context Scraper (SERP & Grounding) (`neon_innovation_lab/ai-search-rag-scraper`) Actor

Perform real-time web search and extract clean organic results, snippet descriptions, and token-efficient markdown context for AI agents and LLM grounding.

- **URL**: https://apify.com/neon\_innovation\_lab/ai-search-rag-scraper.md
- **Developed by:** [Neon Innovation Lab](https://apify.com/neon_innovation_lab) (community)
- **Categories:** AI, Developer tools, SEO tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$20.00 / 1,000 ai web search & rag grounding queries

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/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

## AI Web Search & RAG Context Scraper (Bing SERP / LLM Grounding)

A lightweight, high-performance web search scraper engineered specifically for **AI Agents**, **RAG pipelines**, and **LLM prompt grounding**. Zero proxy bans.

***

### 🚀 Key Features

- **AI & RAG-Optimized:** Outputs pre-formatted markdown blocks ready for immediate injection into Claude, GPT-4, Cursor, and LangChain/LlamaIndex.
- **Organic Results & Snippets:** Clean extraction of page titles, URLs, and contextual descriptions.
- **No Proxy Fees:** Built with optimized Cheerio crawling that avoids heavy browser overhead and Google SERP bans.
- **Ultra-Low Latency:** Processes queries in parallel in under 2 seconds.
- **Pay-Per-Result:** Pay only $0.0015 per query processed.

***

### 📥 Input Example

```json
{
  "queries": [
    "best AI agent frameworks 2026",
    "enterprise MCP servers"
  ],
  "maxResultsPerQuery": 10,
  "formatAsRAGMarkdown": true
}
```

***

### 📤 Output Format

```json
{
  "query": "best AI agent frameworks 2026",
  "rank": 1,
  "title": "Top Autonomous AI Agent Frameworks in 2026",
  "url": "https://example.com/ai-frameworks-2026",
  "snippet": "A comprehensive review of multi-agent architectures, MCP protocol support, and production benchmarks...",
  "ragMarkdown": "### [Top Autonomous AI Agent Frameworks in 2026](https://example.com/ai-frameworks-2026)\nA comprehensive review of multi-agent architectures...",
  "scrapedAt": "2026-09-04T03:15:00.000Z"
}
```

# Actor input Schema

## `queries` (type: `array`):

List of search queries to scrape for AI grounding and RAG context.

## `maxResultsPerQuery` (type: `integer`):

Maximum number of organic search results per query.

## `formatAsRAGMarkdown` (type: `boolean`):

Output pre-formatted markdown blocks ready for immediate prompt injection into Claude, GPT-4, or Cursor.

## Actor input object example

```json
{
  "queries": [
    "best AI agent frameworks 2026",
    "top enterprise MCP servers"
  ],
  "maxResultsPerQuery": 10,
  "formatAsRAGMarkdown": true
}
```

# 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 = {
    "queries": [
        "best AI agent frameworks 2026",
        "top enterprise MCP servers"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("neon_innovation_lab/ai-search-rag-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 = { "queries": [
        "best AI agent frameworks 2026",
        "top enterprise MCP servers",
    ] }

# Run the Actor and wait for it to finish
run = client.actor("neon_innovation_lab/ai-search-rag-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 '{
  "queries": [
    "best AI agent frameworks 2026",
    "top enterprise MCP servers"
  ]
}' |
apify call neon_innovation_lab/ai-search-rag-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,neon_innovation_lab/ai-search-rag-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/p0MO8Z3wqV6mQup43/builds/BYelCEd0aDsn4UrbG/openapi.json