Detect underpriced MLS properties with GPT and alert via Gmail and Slack

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1. Workflow Overview

How It Works This workflow automates competitive real estate pricing analysis by combining multiple MLS data sources with AI powered market intelligence. Designed for real estate professionals, pro...

Best for

Market Research automation workflows
AI Summarization automation workflows
advanced n8n builders looking for reusable templates

Tools used

n8n-nodes-base.scheduletrigger, n8n-nodes-base.set, n8n-nodes-base.httprequest, n8n-nodes-base.merge, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.outputparserstructured, @n8n/n8n-nodes-langchain.agenttool, n8n-nodes-base.if

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.

Original n8n.io source

1.1 Workflow description

Title: Detect underpriced MLS properties with GPT and alert via Gmail and Slack
Workflow name: Detect underpriced MLS properties with GPT and alert via Gmail and Slack

How It Works

This workflow automates competitive real estate pricing analysis by combining multiple MLS data sources with AI-powered market intelligence. Designed for real estate professionals, property managers, and investment analysts, it solves the critical challenge of identifying underpriced properties in competitive markets where manual analysis is time-consuming and prone to oversight. The system fetches listings from multiple MLS platforms, consolidates market data, and deploys specialized AI agents for dual-layer analysis. The Pricing Agent evaluates individual property valuations against market comparables, while the Market Research Agent provides broader market context and trend insights. When underpriced opportunities are detected, automated alerts are dispatched via email and Slack, enabling rapid response to market opportunities. Operating on a daily schedule, this workflow transforms hours of manual research into automated intelligence delivery.

Setup Steps

Configure MLS API credentials in "Fetch MLS Data" and "Fetch Recent Sales Data" nodes
Add OpenAI API key in "OpenAI Model - Pricing Agent"
Set Gmail SMTP credentials in "Send Underpriced Alert Email" node with recipient addresses
Configure Slack webhook URL in "Send Slack Alert" node for channel notifications
Adjust "Daily Pricing Update Schedule" cron expression for preferred execution time

Prerequisites

OpenAI API account with GPT-4 access, MLS data provider API credentials

Use Cases

Investment firms identifying acquisition targets, real estate brokerages monitoring competitive listings

Customization

Modify AI agent prompts for specific property types, adjust underpricing threshold percentages

Benefits

Reduces manual research time by 90%, eliminates human bias in valuation analysis

1.2 Logical Blocks

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.

2. Block-by-Block Analysis

Block 1 - Daily Pricing Update Schedule

Type / Role: n8n-nodes-base.scheduleTrigger - scheduleTrigger
Config choices: Version 1.3

Block 2 - Workflow Configuration

Type / Role: n8n-nodes-base.set - set
Config choices: Version 3.4

Block 3 - Fetch MLS Data

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.3

Block 4 - Fetch Recent Sales Data

Type / Role: n8n-nodes-base.httpRequest - httpRequest
Config choices: Version 4.3

Block 5 - Combine All Market Data

Type / Role: n8n-nodes-base.merge - merge
Config choices: Version 3.2

Block 6 - Pricing Analysis Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 3.1

Block 7 - Pricing Output Parser

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.3

Block 8 - Market Research Agent Tool

Type / Role: @n8n/n8n-nodes-langchain.agentTool - agentTool
Config choices: Version 3

Block 9 - Research Output Parser

Type / Role: @n8n/n8n-nodes-langchain.outputParserStructured - outputParserStructured
Config choices: Version 1.3

Block 10 - Check for Underpriced Properties

Type / Role: n8n-nodes-base.if - if
Config choices: Version 2.3

Block 11 - Send Underpriced Alert Email

Type / Role: n8n-nodes-base.gmail - gmail
Config choices: Version 2.2

Block 12 - Send Slack Alert

Type / Role: n8n-nodes-base.slack - slack
Config choices: Version 2.4

Block 13 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 14 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 15 - Sticky Note2

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 16 - Sticky Note3

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 17 - Sticky Note4

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 18 - Sticky Note5

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 19 - Sticky Note6

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 20 - OpenRouter Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices: Version 1

Block 21 - OpenRouter Chat Model1

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenRouter - lmChatOpenRouter
Config choices: Version 1

3. Summary Table

Workflow	Detect underpriced MLS properties with GPT and alert via Gmail and Slack
Complexity	advanced
Nodes	21
Categories	Market Research, AI Summarization
Author	Cheng Siong Chin
Published	30 Mar 2026

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/14469/14469.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

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.

Download workflow JSON Original n8n.io source Market Research workflows AI Summarization workflows

Frequently asked questions

What does Detect underpriced MLS properties with GPT and alert via Gmail and Slack do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

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.

Cheng Siong Chin

203 workflows

Nodes

n8n-nodes-base.scheduletrigger n8n-nodes-base.set n8n-nodes-base.httprequest n8n-nodes-base.merge @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.outputparserstructured @n8n/n8n-nodes-langchain.agenttool n8n-nodes-base.if

Complexity

advanced

Published 30 Mar 2026

Likes 0

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Install path: /data/workflows/14469/14469.json

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Detect underpriced MLS properties with GPT and alert via Gmail and Slack

Workflow preview

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

How It Works

Setup Steps

Prerequisites

Use Cases

Customization

Benefits

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Daily Pricing Update Schedule

Block 2 - Workflow Configuration

Block 3 - Fetch MLS Data

Block 4 - Fetch Recent Sales Data

Block 5 - Combine All Market Data

Block 6 - Pricing Analysis Agent

Block 7 - Pricing Output Parser

Block 8 - Market Research Agent Tool

Block 9 - Research Output Parser

Block 10 - Check for Underpriced Properties

Block 11 - Send Underpriced Alert Email

Block 12 - Send Slack Alert

Block 13 - Sticky Note

Block 14 - Sticky Note1

Block 15 - Sticky Note2

Block 16 - Sticky Note3

Block 17 - Sticky Note4

Block 18 - Sticky Note5

Block 19 - Sticky Note6

Block 20 - OpenRouter Chat Model

Block 21 - OpenRouter Chat Model1

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions