This content originally appeared on DEV Community and was authored by Yulia Dmitrievna
What I Built
As an independent musician, I spend a lot of time on manual search for venues. Scrolling through websites and looking for contact data takes a lot of time needed for creative work. I built an AI-powered venue discovery tool that analyses musician and venue websites and automatically finds performance opportunities.
The n8n workflow is available at: https://gist.github.com/yulia-n8n/e790102fdcb6af5fc9dbf5a31886290d
The Airtable is publicly shared: https://airtable.com/appfBx8WBRfqCvLab/shrTQd0xYMt5jtG55
The video will be uploaded soon.
What does it do?
The n8n music event aggregator is tool that:
• Scrapes concert pages from musician and venue websites using Bright Data
• Uses n8n AI agent node to extract venue names, locations, dates, and contact information
• Automatically discovers new musicians and venues from the extracted data
• Builds a powerful database of performance opportunities
• Removes duplicates through intelligent AI comparison
• Runs continuously on scheduled triggers to keep the database fresh
*This tool aims to solve the core problem every independent musician faces: finding venues is time-consuming manual work that takes time away from creating music. *
Technical Implementation
The agent consists of three workflows:
Core venue extraction pipeline
- Trigger: Manual start or run on schedule
- Data Source: Airtable databases for Musicians and Venues with “Pending” status
- Web Scraping: Bright Data extracts raw HTML from concert/event pages
- AI Processing: Claude 3.7 Sonnet analyzes content using structured output parsing
- Database Storage: Venue opportunities saved to “Extracted Events” table
Smart Deduplication System
- AI Comparison: LLM compares new discoveries against existing database
- Duplicate Detection: Handles variations in spelling, formatting, and venue names
- Auto-Creation: New musicians/venues automatically added with “New” status
- Status Tracking: Processed sources marked as “Completed” to prevent reprocessing
Source Discovery Automation
- Google Search Integration: SerpApi finds concert pages for new musicians/venues
- URL Collection: Event page URLs automatically added to database records
- Status Updates: Sources moved from “New” to “Pending” for processing
- Continuous Loop: System continuously discovers and processes new opportunities
AI Model Configuration
• Model: Claude 3.7 Sonnet via OpenRouter
• Temperature: 0.1 for
• Output Format: Structured JSON schema with defined fields
• System Instructions: Optimized for venue/contact information extraction
Bright Data Verified Node
Bright Data node handles web scraping of event webpages for further AI specific data extraction.
Inspiration
Like most independent musicians, I spend more time booking gigs than making music. Each venue requires individual research – finding their event calendar, understanding their booking process, identifying the right contact person.
This tool is aimed to solve my personal problem while potentially creating a pipeline that scales to help other independent musicians. Instead of spending weekends researching venues, artists would spend them writing songs. A database would constantly update performance opportunities.
This content originally appeared on DEV Community and was authored by Yulia Dmitrievna