# RAG Web Browser & Web Search API for AI Agents (`bulkleads/web-search-for-ai-agents`) Actor

Web search for AI agents and RAG: search the web and get the top result pages back as clean text for LLMs. A RAG Web Browser alternative at $1.26 per 1,000 pages. Use it as an MCP tool or from LangChain.

- **URL**: https://apify.com/bulkleads/web-search-for-ai-agents.md
- **Developed by:** [bulkleads](https://apify.com/bulkleads) (community)
- **Categories:** AI, Developer tools
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

$1.26 / 1,000 pages

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?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

**Web Search for AI Agents** is a **RAG web browser**: it runs a web search and returns the top result pages as plain text: URL, title, description and the page's visible text, ready for an LLM, a RAG pipeline or an AI agent. It costs **$1.26 per 1,000 pages read**, and pages that fail to load are free.

### How to use it

1. Enter a **Search query**.
2. Choose how many **Pages to read** (1 to 10) and the **Max characters per page**.
3. Click **Start**, or call it as a tool from the Apify MCP server.

### Output example

```json
{
  "query": "cold email subject line best practices",
  "search_position": 1,
  "url": "https://example.com/blog/subject-lines",
  "title": "How to Write Cold Email Subject Lines",
  "text": "Keep subject lines under six words...",
  "ok": true
}
```

### Why use it with an AI agent?

- **One call, search plus reading:** the agent gets page text, not just links.
- **Plain text:** scripts, styles and menus are stripped; headings and paragraphs stay.
- **Predictable cost:** a flat price per page read, with failures free.

### Input reference

- `query`: the search terms, as a person would type them
- `maxResults`: pages to read, 1 to 10 (default 3)
- `maxChars`: characters of text kept per page, 1,000 to 30,000 (default 15,000)

Each page comes back as its own dataset item with its search position, so an agent can cite the source it used.

### How much does it cost?

**$1.26 per 1,000 pages.** A search that reads 3 pages costs under a cent.

### FAQ

**Is this a RAG Web Browser alternative?** Yes. It searches the web and returns the top pages as text for your LLM or agent, paid per page read.

**Can I use it in Claude, ChatGPT or Cursor?** Yes, through the Apify MCP server.

### Related actors

Extract structured fields from pages with [AI Web Scraper](https://apify.com/bulkleads/ai-web-scraper). Get raw search results with [DuckDuckGo Scraper](https://apify.com/bulkleads/duckduckgo-scraper).

# Actor input Schema

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

Search query.

## `maxResults` (type: `integer`):

Pages to read.

## `maxChars` (type: `integer`):

Max characters per page.

## Actor input object example

```json
{
  "query": "best practices for cold email subject lines",
  "maxResults": 3,
  "maxChars": 15000
}
```

# 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 = {
    "query": "best practices for cold email subject lines"
};

// Run the Actor and wait for it to finish
const run = await client.actor("bulkleads/web-search-for-ai-agents").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": "best practices for cold email subject lines" }

# Run the Actor and wait for it to finish
run = client.actor("bulkleads/web-search-for-ai-agents").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 '{
  "query": "best practices for cold email subject lines"
}' |
apify call bulkleads/web-search-for-ai-agents --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,bulkleads/web-search-for-ai-agents"
        }
    }
}
```

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/2GB2E6odwd3VKctZb/builds/67gSCtFeXXdPb0yVR/openapi.json