Block 1 - When clicking ‘Test workflow’
- Type / Role
- n8n-nodes-base.manualTrigger - manualTrigger
- Config choices
- Version 1
This workflow is provided as-is. Please review and test before using in production.
Notice Community nodes can only be installed on self hosted instances of n8n. Who this is ...
n8n-nodes-base.manualtrigger, n8n-nodes-mcp.mcpclient, n8n-nodes-base.set, @n8n/n8n-nodes-langchain.informationextractor, n8n-nodes-base.merge, n8n-nodes-base.function, n8n-nodes-base.httprequest, n8n-nodes-base.readwritefile
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Ranjan Dailata.
Original n8n.io sourceCommunity nodes can only be installed on self-hosted instances of n8n.
This workflow automates the real-time extraction of Job Descriptions and Salary Information from job listing pages using Bright Data MCP and analyzes content using OpenAI GPT-4o mini.
This workflow is ideal for:
Recruiters & HR Tech Startups: Automate job data collection from public listings
Market Intelligence Teams: Analyze compensation trends across companies or geographies
Job Boards & Aggregators: Power search results with structured, enriched listings
AI Workflow Builders: Extend to other career platforms or automate resume-job match analysis
Analysts & Researchers: Track hiring signals and salary benchmarks in real time
Traditional scraping of job portals can be challenging due to cluttered content, anti-scraping measures, and inconsistent formatting. Manually analyzing salary ranges and job descriptions is tedious and error-prone.
This workflow solves the problem by:
Simulating user behavior using Bright Data MCP Client to bypass anti-scraping systems
Extracting structured, clean job data in Markdown format
Using OpenAI GPT-4o mini to analyze and extract precise salary details and refined job descriptions
Merging and formatting the result for easy consumption
Delivering final output via webhook, Google Sheets, or file system
Components & Flow
Input Nodes
job_search_url: The job listing or search result URL
job_role: The title or role being searched for (used in logging/formatting)
MCP Client Operations
MCP Salary Data Extractor
Simulates browser behavior and scrapes salary-related content (if available)
MCP Job Description Extractor
Extracts full job description as structured Markdown content
OpenAI GPT-4o mini Nodes
Salary Information Extractor
Job Description Refiner
Company Information Extractor
Merge Node
Aggregate node
Final Output Handling
The output is handled in three different formats depending on your downstream needs:
Save to Disk
Google Sheet Update
Webhook Notification
Make sure to copy the Bright Data API_TOKEN within the Environments textbox above as API_TOKEN=<your-token>
Modify Input Source
Change the job_search_url to point to any job board or aggregator
Customize job_role to reflect the type of jobs being analyzed
Tweak LLM Prompts (Optional)
Change Output Format
Customize the merged object to output JSON, CSV, or Markdown based on downstream needs
Add additional destinations (e.g., Slack, Airtable, Notion) via n8n nodes
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
| Workflow | Real-time extract of job, company, salary details via Bright Data MCP & OpenAI |
|---|---|
| Complexity | advanced |
| Nodes | 22 |
| Categories | Market Research, AI Summarization |
| Author | Ranjan Dailata |
| Published | 09 Jun 2025 |
Use the JSON export at /data/workflows/4829/4829.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
Notice Community nodes can only be installed on self hosted instances of n8n. Who this is ...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Market Research, AI Summarization use case.