This n8n workflow retrieves AI agent chat memory logs stored in Postgres and pushes them to Google Sheets, creating one sheet per session. It’s useful for teams building chat-based products or agents and needing to review or analyze session logs in a collaborative format.
n8n_chat_histories
table with an AI Agent connected to it. If you need an example, you can follow this tutorialcreated_at
column (see Setup > Add a datetime column)This workflow expects a Google Sheets file where each session will be stored in its own tab.
A basic tab layout is duplicated and renamed with the session ID.
👉 Use this template as a starting point
Note: You can hide the template after the first tabs have been created
Trigger
The workflow can be launched manually or on a schedule (e.g. daily at noon).
Retrieve sessions
Runs a SQL query to get distinct session_id
values from the n8n_chat_histories
table.
Loop over sessions
For each session:
session_id
.Fetch messages
Selects all messages linked to the session from Postgres.
Append to sheet
Adds each message to the Google Sheet with columns:
user
, assistant
, etc.)created_at
, formatted yyyy-MM-dd hh:mm:ss
user_id
) by overriding session_id
in your memory config.