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Scrape Web Data with Bright Data, Google Gemini and MCP Automated AI Agent

Ranjan DailataRanjan Dailata
3911 views
2/3/2026
Lead GenerationJotFormAutomationSalesforceCRM
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Disclaimer

This template is only available on n8n self-hosted as it's making use of the community node for MCP Client.

Scrape Web Data with Bright Data MCP Client.png

Who this is for?

The Scrape Web Data with Bright Data and MCP Automated AI Agent workflow is built for professionals who need to automate large-scale, intelligent data extraction by utilizing the Bright Data MCP Server and Google Gemini.

This solution is ideal for:

  1. Data Analysts - Who require structured, enriched datasets for analysis and reporting.

  2. Marketing Researchers - Seeking fresh market intelligence from dynamic web sources.

  3. Product Managers - Who want competitive product and feature insights from various websites.

  4. AI Developers - Aiming to feed web data into downstream machine learning models.

  5. Growth Hackers - Looking for high-quality data to fuel campaigns, research, or strategic targeting.

What problem is this workflow solving?

Manually scraping websites, cleaning raw HTML data, and generating useful insights from it can be slow, error-prone, and non-scalable.

This workflow solves these problems by:

  1. Automating complex web data extraction through Bright Data’s MCP Server.

  2. Reducing the human effort needed for cleaning, parsing, and analyzing unstructured web content.

  3. Allowing seamless integration into further automation processes.

What this workflow does?

This n8n workflow performs the following steps:

  1. Trigger: Start manually.

  2. Input URL(s): Specify the URL to perform the web scrapping.

  3. Web Scraping (Bright Data): Use Bright Data’s MCP Server tools to accomplish the web data scrapping with markdown and html format.

  4. Store / Output: Save results into disk and also performs a Webhook notification.

Setup

  1. Please make sure to setup n8n locally with MCP Servers by navigating to n8n-nodes-mcp
  2. Please make sure to install the Bright Data MCP Server @brightdata/mcp on your local machine.
  3. Sign up at Bright Data.
  4. Create a Web Unlocker proxy zone called mcp_unlocker on Bright Data control panel.
  5. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions.
  6. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy).
  7. In n8n, configure the credentials to connect with MCP Client (STDIO) account with the Bright Data MCP Server as shown below.

MCPClientAccount.png

Make sure to copy the Bright Data API_TOKEN within the Environments textbox above as API_TOKEN=<your-token>. 8. Update the LinkedIn URL person and company workflow. 9. Update the Webhook HTTP Request node with the Webhook endpoint of your choice. 10. Update the file name and path to persist on disk.

How to customize this workflow to your needs

  1. Different Inputs: Instead of static URLs, accept URLs dynamically via webhook or form submissions.

  2. Outputs: Update the Webhook endpoints to send the response to Slack channels, Airtable, Notion, CRM systems, etc.

Scrape Web Data with Bright Data, Google Gemini, and n8n Automated AI Agent

This n8n workflow leverages the power of Bright Data for web scraping, Google Gemini for AI-driven analysis, and an n8n AI Agent to automate the entire process. It's designed to efficiently extract web data, process it with a large language model, and store the results.

What it does

This workflow automates the following steps:

  1. Manual Trigger: Initiates the workflow manually, allowing for on-demand execution.
  2. Edit Fields (Set): Prepares the input data for the AI Agent, likely defining the scraping task or initial prompt.
  3. AI Agent (LangChain): Acts as an intelligent orchestrator. It uses a "Plan and Execute" strategy to determine the best course of action based on the input.
    • Simple Memory: Provides conversational memory to the AI Agent, allowing it to maintain context throughout the interaction.
    • Google Gemini Chat Model: Serves as the large language model (LLM) for the AI Agent, enabling it to understand instructions, generate plans, and process information.
    • HTTP Request: This is likely the tool the AI Agent uses to interact with the Bright Data API for web scraping.
    • Function: A custom code block that the AI Agent can utilize for specific data manipulation or logic not covered by other tools.
    • Read/Write Files from Disk: Another tool available to the AI Agent, potentially for storing intermediate results or final output locally.
  4. Sticky Note: Provides a visual note within the workflow, likely for documentation or instructions.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n instance: A running n8n instance (cloud or self-hosted).
  • Bright Data Account: An account with Bright Data to access their web scraping services. You'll need API credentials.
  • Google Gemini API Key: Access to the Google Gemini API for the chat model.
  • n8n LangChain Nodes: Ensure the @n8n/n8n-nodes-langchain package is installed in your n8n environment.

Setup/Usage

  1. Import the workflow: Download the JSON provided and import it into your n8n instance.
  2. Configure Credentials:
    • Bright Data: Set up an HTTP Request credential in n8n for your Bright Data API.
    • Google Gemini: Configure a Google Gemini credential in n8n with your API key.
  3. Review and Customize:
    • Edit Fields (Set): Adjust the input data to define your specific web scraping task and the information you want the AI Agent to extract or analyze.
    • AI Agent: While the core structure is set, you might want to review the agent's prompt or available tools based on your specific use case.
    • HTTP Request (within AI Agent): Ensure the HTTP Request node within the AI Agent is correctly configured to interact with the Bright Data API for your scraping needs. This might involve setting up specific URLs, headers, or body content depending on the Bright Data product you are using (e.g., Web Scraper IDE, Data Collector).
    • Function (within AI Agent): If the AI Agent is intended to use custom JavaScript logic, ensure the code in the "Function" node is appropriate for your needs.
    • Read/Write Files from Disk (within AI Agent): If the AI Agent needs to interact with local files, ensure the paths and operations are correctly defined.
  4. Execute the workflow: Click the "Execute workflow" button on the "Manual Trigger" node to run the workflow. The AI Agent will then take over, using Bright Data to scrape the web and Google Gemini to process the information.

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