Monitor & alert on social media ad performance with Bright Data MCP
UnknownUnknown. This template uses community nodes we can't verify statically. Uses community nodes that can't be verified statically (unverified community packages are off by default in 3.0). Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 12 nodes and runs on a schedule (every hour). Along the way it connects OpenAI Chat Model, Gmail and Mcp (community).
How it runs
Trigger: On a schedule (every hour).
- 📥 Set facebook ad dashboard URL (Edit Fields (Set)): sets 1 field: url
- 🧠 Scrape Ads via MCP Agent (AI Agent): runs an AI agent, with model: OpenAI Chat Model; 1 tool (MCP Client); output parser: Auto-fixing Output Parser
- 🔄 Return One Ad at a Time (Code): runs custom JavaScript code
- 🚨 Is Ad Underperforming? (If): checks a condition and branches into true / false
- 📬 Send Alert Email (Gmail): uses Gmail
Services it uses
Before you upgrade to n8n 3.0
We can't fully verify this one: it relies on 1 community package, and n8n 3.0 turns unverified community packages off by default (N8N_UNVERIFIED_PACKAGES_ENABLED=false).
- Check that n8n-nodes-mcp is verified or supports 3.0 (used in MCP Client).
Nodes used (11)
- OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Mcp Client Tool
n8n-nodes-mcp.mcpClientTool - Schedule Trigger
n8n-nodes-base.scheduleTrigger - Edit Fields (Set)
n8n-nodes-base.set - AI Agent
@n8n/n8n-nodes-langchain.agent - Code
n8n-nodes-base.code - If
n8n-nodes-base.if - Gmail
n8n-nodes-base.gmail - No Operation, do nothing
n8n-nodes-base.noOp - Auto-fixing Output Parser
@n8n/n8n-nodes-langchain.outputParserAutofixing - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured
From the author
This workflow automatically monitors social media advertising performance across platforms to track campaign effectiveness and ROI. It saves you time by eliminating the need to manually check multiple ad platforms and provides consolidated performance data…