Weaviate now offers a community node for n8n that enables no-code AI agent workflows with vector database integration. The integration provides four core functionalities: querying documents, inserting data, retrieving documents for chains, and using documents as agent tools. A practical example demonstrates building an automated AI trend analysis system that scrapes arXiv papers, enriches them with LLM classifications, stores embeddings in Weaviate, and uses an AI agent to generate weekly research trend summaries via email. The workflow showcases how vector stores enhance AI agent capabilities by providing grounded context beyond simple prompting.
Table of contents
The Weaviate Community Node for n8n Building an Agentic Workflow with Weaviate and n8n to Keep Up with AI Trends Part 1: Fetch, Clean, Enrich and Insert arXiv Abstracts into Weaviate Part 2: Use Agentic RAG to Identify Research Trends and Send Them in an Email. Workflow Output Conclusion Resource Guide Sort: