
RAG Web Browser
Pricing
Pay per usage

RAG Web Browser
Web browser for OpenAI Assistants, RAG pipelines, or AI agents, similar to a web browser in ChatGPT. It queries Google Search, scrapes the top N pages, and returns their content as Markdown for further processing by an LLM. It can also scrape individual URLs. Supports Model Context Protocol (MCP).
4.3 (10)
Pricing
Pay per usage
99
Total users
3K
Monthly users
988
Runs succeeded
>99%
Issues response
4.7 days
Last modified
a month ago
You can access the RAG Web Browser programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, youβll need an Apify account and your API token, found in Integrations settings in Apify Console.
{ "mcpServers": { "local-actors-mcp-server": { "command": "npx", "args": [ "-y", "@apify/actors-mcp-server", "--actors", "apify/rag-web-browser" ], "env": { "APIFY_TOKEN": "<YOUR_API_TOKEN>" } } }}
Configure MCP server with RAG Web Browser
You can interact with the MCP server via standard input/output - stdio (as shown above), which is ideal for local integrations and command-line tools such as the Claude desktop client, or you can interact with the server through Server-Sent Events (SSE) to send messages and receive responses, which looks as follows:
{ "mcpServers": { "remote-actors-mcp-server": { "type": "sse", "url": "https://mcp.apify.com/sse?actors=apify/rag-web-browser", "headers": { "Authorization": "Bearer <YOUR_API_TOKEN>" } } }}
You can connect to the Apify MCP Server using clients like Tester MCP Client, or any other supported MCP client of your choice.
If you want to learn more about our Apify MCP implementation, check out our MCP documentation. To learn more about the Model Context Protocol in general, refer to the official MCP documentation or read our blog post.