Model Context Protocol (MCP) Server for the RAG Web Browser Actor
Implementation of an MCP server for the RAG Web Browser Actor.
This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.
<a href="https://glama.ai/mcp/servers/sr8xzdi3yv"><img width="380" height="200" src="https://glama.ai/mcp/servers/sr8xzdi3yv/badge" alt="mcp-server-rag-web-browser MCP server" /></a>
What does this MCP server do?
This server is specifically designed to provide fast responses to AI agents and LLMs, allowing them to interact with the web and extract information from web pages.
It runs locally and communicates with the RAG Web Browser Actor in **Standby mode**,
sending search queries and receiving extracted web content in response.
The RAG Web Browser Actor allows an AI assistant to:
- Perform web search, scrape the top N URLs from the results, and return their cleaned content as Markdown
- Fetch a single URL and return its content as Markdown
Components
Tools
- search: Query Google Search, scrape the top N URLs from the results, and returns their cleaned content as Markdown. Arguments:
What is the Model Context Protocol?
The Model Context Protocol (MCP) is a framework that enables AI applications, such as Claude Desktop, to connect seamlessly with external tools and data sources.
For more details, visit the Model Context Protocol website or read the blog post What is MCP and why does it matter?.
How does the MCP Server integrate with AI Agents?
The MCP Server empowers AI Agents to perform web searches and browsing using the RAG Web Browser Actor.
For a comprehensive understanding of AI Agents, check out our blog post: What are AI Agents? and explore Apify's Agents.
Interested in building and monetizing your own AI agent on Apify? Check out our step-by-step guide for creating, publishing, and monetizing AI agents on the Apify platform.
Related MCP servers and clients by Apify
This server operates over standard input/output (stdio), providing a straightforward connection to AI Agents. Apify offers several other MCP-related tools:
Server Options
- ** This MCP Server** A local stdio-based server for direct integration with Claude Desktop
- ** RAG Web Browser Actor via SSE** Access the RAG Web Browser directly via Server-Sent Events without running a local server
- ** MCP Server Actor** MCP Server that provides AI agents with access to over 4,000 specialized Apify Actors
Client Options
- ** Tester MCP Client** A user-friendly UI for interacting with any SSE-based MCP server
Configuration
Prerequisites
- MacOS or Windows
- The latest version of Claude Desktop must be installed (or another MCP client)
- Node.js (v18 or higher)
- Apify API Token (
APIFY_TOKEN)
Install
Follow the steps below to set up and run the server on your local machine:
First, clone the repository using the following command:
Navigate to the project directory and install the required dependencies:
Before running the server, you need to build the project:
Claude Desktop
Configure Claude Desktop to recognize the MCP server.
- Open your Claude Desktop configuration and edit the following file:
- Restart Claude Desktop
- Examples You can ask Claude to perform web searches, such as:
Debug the server using the MCP Inspector
Development
Local client (stdio)
To test the server locally, you can use
example_client_stdio.ts:The script will start the MCP server, fetch available tools, and then call the
search tool with a query.Direct API Call
To test calling the RAG Web Browser Actor directly:
Debugging
Since MCP servers operate over standard input/output (stdio), debugging can be challenging.
For the best debugging experience, use the MCP Inspector.
Build the mcp-server-rag-web-browser package:
You can launch the MCP Inspector via `npm` with this command:
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.
Model Context Protocol (MCP) Server for the RAG Web Browser Actor
Implementation of an MCP server for the RAG Web Browser Actor.
This Actor serves as a web browser for large language models (LLMs) and RAG pipelines, similar to a web search in ChatGPT.
<a href="https://glama.ai/mcp/servers/sr8xzdi3yv"><img width="380" height="200" src="https://glama.ai/mcp/servers/sr8xzdi3yv/badge" alt="mcp-server-rag-web-browser MCP server" /></a>
What does this MCP server do?
This server is specifically designed to provide fast responses to AI agents and LLMs, allowing them to interact with the web and extract information from web pages.
It runs locally and communicates with the RAG Web Browser Actor in **Standby mode**,
sending search queries and receiving extracted web content in response.
The RAG Web Browser Actor allows an AI assistant to:
- Perform web search, scrape the top N URLs from the results, and return their cleaned content as Markdown
- Fetch a single URL and return its content as Markdown
Components
Tools
- search: Query Google Search, scrape the top N URLs from the results, and returns their cleaned content as Markdown. Arguments:
What is the Model Context Protocol?
The Model Context Protocol (MCP) is a framework that enables AI applications, such as Claude Desktop, to connect seamlessly with external tools and data sources.
For more details, visit the Model Context Protocol website or read the blog post What is MCP and why does it matter?.
How does the MCP Server integrate with AI Agents?
The MCP Server empowers AI Agents to perform web searches and browsing using the RAG Web Browser Actor.
For a comprehensive understanding of AI Agents, check out our blog post: What are AI Agents? and explore Apify's Agents.
Interested in building and monetizing your own AI agent on Apify? Check out our step-by-step guide for creating, publishing, and monetizing AI agents on the Apify platform.
Related MCP servers and clients by Apify
This server operates over standard input/output (stdio), providing a straightforward connection to AI Agents. Apify offers several other MCP-related tools:
Server Options
- ** This MCP Server** A local stdio-based server for direct integration with Claude Desktop
- ** RAG Web Browser Actor via SSE** Access the RAG Web Browser directly via Server-Sent Events without running a local server
- ** MCP Server Actor** MCP Server that provides AI agents with access to over 4,000 specialized Apify Actors
Client Options
- ** Tester MCP Client** A user-friendly UI for interacting with any SSE-based MCP server
Configuration
Prerequisites
- MacOS or Windows
- The latest version of Claude Desktop must be installed (or another MCP client)
- Node.js (v18 or higher)
- Apify API Token (
APIFY_TOKEN)
Install
Follow the steps below to set up and run the server on your local machine:
First, clone the repository using the following command:
Navigate to the project directory and install the required dependencies:
Before running the server, you need to build the project:
Claude Desktop
Configure Claude Desktop to recognize the MCP server.
- Open your Claude Desktop configuration and edit the following file:
- Restart Claude Desktop
- Examples You can ask Claude to perform web searches, such as:
Debug the server using the MCP Inspector
Development
Local client (stdio)
To test the server locally, you can use
example_client_stdio.ts:The script will start the MCP server, fetch available tools, and then call the
search tool with a query.Direct API Call
To test calling the RAG Web Browser Actor directly:
Debugging
Since MCP servers operate over standard input/output (stdio), debugging can be challenging.
For the best debugging experience, use the MCP Inspector.
Build the mcp-server-rag-web-browser package:
You can launch the MCP Inspector via `npm` with this command:
Upon launching, the Inspector will display a URL that you can access in your browser to begin debugging.