Milvus + n8n + MCP: Build Voice AI Real Estate Agent (Hybrid Search Tutorial)

Learn to build a production-ready Voice AI Real Estate Agent using Milvus vector database, n8n workflows, and Model Context Protocol (MCP). This tutorial covers hybrid search (semantic + keyword + image), GoHighLevel integration, and Railway deployment. 🚀 What You'll Build: A voice AI agent that understands natural language, searches property images using CLIP embeddings, and delivers results in under 10 milliseconds. 🛠️ Tech Stack: • Milvus - Open-source vector database (40,000+ GitHub stars) - https://github.com/milvus-io/milvus - Zilliz Cloud (managed Milvus) - https://tinyurl.com/zilliz-cloud • n8n - Workflow automation platform - n8n.io • MCP (Model Context Protocol) - AI agent tool integration • GoHighLevel - AI voice agent platform - https://www.gohighlevel.com/ • Railway - Cloud deployment template - https://railway.com/deploy/milvus-rest-api?referralCode=mPreNM&utm_medium=integration&utm_source=template&utm_campaign=generic Resources • Script to generate sample data: https://github.com/flex123/milvus-scripts • n8n workflow: https://drive.google.com/file/d/1Kltir7NNOZKRCfGtb9Rgr-FVnOmXjWXx/view?usp=drive_link ⚡ Key Features: ✅ Hybrid Search - Combines semantic, keyword, AND image similarity ✅ Text-to-Image Search - Find properties by describing photos ("modern kitchen") ✅ Sub-10ms Latency - Production-grade performance ✅ Horizontal Scalability - Architecture that scales to billions of vectors ✅ One-Click Deploy - Railway template with all services configured ✅ Multi-Modal AI - Search text descriptions AND property photos simultaneously