memory

Custom memory node for n8n AI Agent with external API support

Package Information

Released: 9 mo ago
Downloads: 20 weekly / 69 monthly
Latest Version: 0.6.3
Author: Filipe Labs

Available Nodes

Memory API
Use an external API as chat memory storage
Memory Workflow
Use a sub-workflow as chat memory storage

Documentation

n8n-nodes-memory

Custom memory nodes for n8n AI Agent with workflow-based storage.

Two Nodes

Node Use Case
Memory API External webhook/API as memory backend
Memory Workflow Sub-workflow within n8n as memory backend

The Power: Memory as Workflows

Traditional memory nodes are passive storage. This node transforms memory into event-driven workflows - each memory operation (get, add, clear) can trigger complete n8n workflows with access to 400+ integrations.

On GET (before AI responds)

  • Fetch context from vector databases (RAG)
  • Load user preferences from CRM
  • Inject real-time data (weather, stocks, news)
  • Summarize old conversations automatically
  • Generate dynamic context with another AI
  • Apply predictive loading for likely questions

On ADD (after each message)

  • Analyze sentiment in real-time
  • Extract entities and intents
  • Update user profiles and CRM records
  • Create tasks/tickets automatically
  • Trigger notifications and alerts
  • Route to different AI agents based on intent
  • Build knowledge graphs from conversations
  • Feed training data pipelines

On CLEAR (end of session)

  • Generate conversation summaries
  • Extract action items
  • Send follow-up emails
  • Archive to compliance systems
  • Update customer journey stages

Use Cases

Self-Evolving AI - Behavior rules that adapt based on conversation patterns. Detect frustration, switch to empathetic mode.

Multi-Agent Orchestration - Route messages to specialized agents. One memory feeding an agent swarm.

Memory as API Gateway - Natural language interface to any system. "Check my order status" triggers lookup workflows.

Semantic Compression - Compress long exchanges into dense summaries, expand on retrieval. Effectively infinite context window.

Cross-Platform Identity - Sync across WhatsApp, Telegram, Web. Same AI remembers you everywhere.

Conversation Branching - Create save points, fork conversations, explore different paths. Git for chat.

Regulatory Firewall - Check compliance before storing, redact sensitive info based on user role. GDPR/LGPD by design.

Continuous Learning - Route high-quality exchanges to training datasets. Self-improving system.

Social Graph Memory - Map relationships mentioned in conversations. Build knowledge graphs of user's world.

Emotional State Machine - Track emotional journey, maintain consistent AI "mood" across sessions.

Installation

npm install n8n-nodes-memory

Then restart n8n.

Setup

  1. Create a Memory API workflow - A webhook that handles get, add, and clear actions
  2. Set up your storage - PostgreSQL, Redis, or any backend
  3. Connect to AI Agent - Link the Memory API node to your agent's memory input

API Contract

Your webhook must handle POST requests with:

Action Purpose Returns
get Retrieve messages for session { messages: [{ type, content }, ...] }
add Store a message { success: true }
clear Clear session history { success: true }

Message types: human or ai

Parameters

Memory API

Parameter Description
API URL Your memory webhook URL
Session ID Unique conversation identifier
API Key Optional Bearer token
Context Window Length Messages to include (default: 10)

Memory Workflow

Parameter Description
Workflow ID ID of the sub-workflow to execute
Session ID Unique conversation identifier
Context Window Length Messages to include (default: 10)

How It Works

Implements LangChain's BaseListChatMessageHistory with BufferWindowMemory. The AI Agent calls your workflows automatically during conversation.

License

MIT

Author

Filipe Labs

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