# Turn a web search into Markdown for an AI agent

**Use case:** 

Search for Apify public Actor tasks and return one clean Markdown result for a retrieval or AI-agent workflow.

## Input

```json
{
  "query": "Apify Actor public tasks",
  "urls": [],
  "maxResults": 1,
  "outputFormat": "markdown",
  "lang": "en"
}
```

## Output

```json
{
  "metadata": {
    "label": "Page metadata",
    "format": "object"
  },
  "markdown": {
    "label": "Markdown",
    "format": "string"
  },
  "crawl": {
    "label": "Crawl status",
    "format": "object"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The RAG Web Browser Actor is ready to run with the inputs already set for "Turn a web search into Markdown for an AI agent". [Sign up or log in](https://console.apify.com/create-task-from-example/gqIuTOjrb87m4FHqb) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Turn a web search into Markdown for an AI agent" task

The RAG Web Browser Actor will start running based on the input automatically. You can also change all the input fields, like search query, URLs to extract, and more, to match your specific use case.

### 3. Receive the "Turn a web search into Markdown for an AI agent" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as page metadata, markdown, and crawl status.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Turn a web search into Markdown for an AI agent" task via API](https://apify.com/travelmonitorlab/rag-web-browser.md).

## FAQ

### What does this RAG task return?

It returns one search result processed into clean Markdown for retrieval, summarization or agent context.

### Can it process a URL directly?

Yes. Add public URLs to the urls array or replace the search query in your duplicated task.

## About this Actor

This example demonstrates how to use [RAG Web Browser](https://apify.com/travelmonitorlab/rag-web-browser.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/travelmonitorlab/rag-web-browser.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

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 full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/travelmonitorlab/rag-web-browser.md

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`).