Complete Airtable database management with AI agents and Redis storage
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 19 nodes and runs when an MCP client calls one of its tools (plus 1 other trigger). Along the way it connects HTTP Request, Redis Chat Memory, OpenAI Chat Model and MCP Client and 1 more. It also calls api.airtable.com over HTTP.
How it runs
Trigger: When an MCP client calls one of its tools (plus 1 other trigger).
- Airtable Agent (AI Agent): runs an AI agent, with model: gpt-5-mini; 5 tools (MCP Client, get_base_id, set_base_id, get_workspace_id…); memory: Redis Chat Memory
Services it uses
HTTP calls to: api.airtable.com
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (8)
- Http Request Tool
n8n-nodes-base.httpRequestTool - Redis Chat Memory
@n8n/n8n-nodes-langchain.memoryRedisChat - AI Agent
@n8n/n8n-nodes-langchain.agent - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - MCP Client Tool
@n8n/n8n-nodes-langchain.mcpClientTool - MCP Server Trigger
@n8n/n8n-nodes-langchain.mcpTrigger - Redis Tool
n8n-nodes-base.redisTool
From the author
What this workflow does Complete Airtable database management system using MCP (Model Context Protocol) for AI agents. Create bases, tables with complex field types, manage records, and maintain state with Redis storage. Setup steps 1. Add your Airtable…