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Extract & search ProductHunt data with Bright Data MCP and Google Gemini AI

Ranjan DailataRanjan Dailata
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2/3/2026
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AI Agent Driven ProductHunt Data Extract Search with Bright Data Google Gemini.png

Notice

Community nodes can only be installed on self-hosted instances of n8n.

Who this is for?

This workflow template enables intelligent data extraction from ProductHunt using Bright Data’s Model Context Protocol (MCP) and processes search results with Google Gemini.

This workflow is designed for individuals and teams who need automated, intelligent discovery and analysis of new tech products. It's especially valuable for:

  • Startup Analysts & VC Researchers
  • Growth Hackers & Marketers
  • Recruiters & Tech Scouts
  • Product Managers & Innovation Teams
  • AI & Automation Enthusiasts

What problem is this workflow solving?

Traditional product discovery on ProductHunt is constrained by limited descriptions and requires repeated manual validation through web searches. Manually extracting and enriching this data is slow, repetitive, and error-prone.

This workflow solves the problem by:

  • Extracting real-time ProductHunt data using Bright Data’s MCP infrastructure to mimic real-user behavior and avoid blocks.

  • Performing contextual searches on Google for a specific product on ProductHunt to gather use cases, reviews, and related information.

  • Structuring results using Google Gemini LLM to provide human-readable insights and reduce noise.

  • Delivering results seamlessly by saving output to disk, updating Google Sheets, and sending Webhook alerts.

What this workflow does

Input Field Node

Define the ProductHunt category with the search term(s) you want to target. This is used to drive extraction and search operations.

Agent Operation Node

The agent performs two major tasks:

  • Extract from ProductHunt Retrieves trending products from ProductHunt using Bright Data MCP

  • Contextual Google Search for the product the agent searches Google for deeper context, including:

    • Reviews

    • Competitor mentions

    • Real-world usage examples

LLM Node (Google Gemini)

  • Analyzes and summarizes extracted web content

  • Removes noise (ads, menus, etc.)

  • Structures content into bullet points, insights, or JSON objects

Pre-conditions

  1. Knowledge of Model Context Protocol (MCP) is highly essential. Please read this blog post - model-context-protocol
  2. You need to have the Bright Data account and do the necessary setup as mentioned in the Setup section below.
  3. You need to have the Google Gemini API Key. Visit Google AI Studio
  4. You need to install the Bright Data MCP Server @brightdata/mcp
  5. You need to install the n8n-nodes-mcp

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>

How to customize this workflow to your needs

This workflow is flexible and modular, allowing you to adapt it for various research, product discovery, or trend analysis use cases. Below are the key customization points and how to modify them.

Define Your Target Products or Topics:

Change the input parameter to a specific ProductHunt category, tag, or keyword (e.g., "AI tools", "SaaS", "DevOps")

Change Output Destinations :

  • Save to Disk: Change the file format (.json, .csv, .md) or directory path

  • Google Sheet: Modify sheet name, structure (columns like Product, Summary, Link)

  • Webhook Notification: Point to a Slack/Discord/CRM/Webhook URL with payload mapping

n8n Workflow: Extract and Search Product Hunt Data with Bright Data and Google Gemini AI

This n8n workflow automates the process of extracting product data from Product Hunt using Bright Data, enriching it with AI-generated insights from Google Gemini, and then storing the processed information.

What it does

This workflow streamlines the following tasks:

  1. Manual Trigger: The workflow is initiated manually.
  2. Function Node (Placeholder): A Function node is present, which typically allows for custom JavaScript code execution to transform or manipulate data. In this workflow, its specific logic would need to be defined.
  3. HTTP Request (Bright Data): Makes an HTTP request, likely to the Bright Data API, to scrape or extract data from Product Hunt.
  4. Edit Fields (Set): Transforms and sets specific fields in the incoming data, preparing it for further processing.
  5. Basic LLM Chain (Google Gemini): Processes the extracted Product Hunt data using a Basic LLM Chain node, leveraging the Google Gemini Chat Model for AI-driven analysis or generation.
  6. Structured Output Parser: Parses the output from the AI model into a structured format, likely JSON, for easier consumption.
  7. AI Agent (Google Gemini): Further processes data using an AI Agent powered by Google Gemini, suggesting more complex AI tasks like summarization, categorization, or sentiment analysis.
  8. Google Sheets: Appends the final, AI-enriched data to a Google Sheet for storage and further analysis.
  9. Read/Write Files from Disk: This node is available but not connected, indicating a potential for saving data to disk or reading configuration from files.
  10. Sticky Note: A sticky note is present for documentation or reminders within the workflow.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • Bright Data Account: An account with Bright Data and the necessary API credentials to perform web scraping.
  • Google Gemini API Key: Access to the Google Gemini API with appropriate authentication.
  • Google Sheets Account: A Google account with access to Google Sheets, and a specific spreadsheet and sheet configured to receive the data.
  • n8n Credentials: Configured n8n credentials for Bright Data, Google Gemini, and Google Sheets.

Setup/Usage

  1. Import the Workflow: Import the provided JSON into your n8n instance.
  2. Configure Credentials:
    • Set up your Bright Data API credentials in the "HTTP Request" node.
    • Configure your Google Gemini API key within the "Google Gemini Chat Model" and "AI Agent" nodes.
    • Provide your Google Sheets credentials and specify the Spreadsheet ID and Sheet Name in the "Google Sheets" node.
  3. Customize Function Node: If the "Function" node contains specific logic for your use case, ensure it is correctly configured.
  4. Execute Workflow: Run the workflow manually by clicking "Execute Workflow" on the "Manual Trigger" node.

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