better-ai-agent

A better AI Agent node for n8n with improved memory management and modern AI SDK integration

Package Information

Released: 6/11/2025
Downloads: 100 weekly / 574 monthly
Latest Version: 1.1.1
Author: fjrdomingues

Available Nodes

Better AI Agent
Advanced AI Agent with improved memory management and modern AI SDK (OpenAI Message Format)

Documentation

Better AI Agent for n8n

An improved AI Agent node for n8n that provides better memory management, modern AI SDK integration and a webhook option to push intermediate messages as they happen.

Features

  • Conversation Memory that includes Tools – every user message, tool call and tool result is stored.
  • Modern AI SDK Providers – wraps OpenAI, Gemini and Anthropic through Vercel AI SDK.
  • Live Streaming Updates: Intermediate Webhook URL lets you push each agent step in real-time

Installation

npm install n8n-nodes-better-ai-agent

Compatibility

This node is designed to be a drop-in replacement for the existing AI Agent node while providing enhanced functionality:

  • ✅ Works with existing Language Model nodes
  • ✅ Works with existing Memory nodes
  • ✅ Works with existing Tool nodes
  • ✅ Works with existing Output Parser nodes
  • ✅ Maintains same input/output interface

Key Improvements Over Standard Agent

1. Memory Management

  • Problem: Original agent doesn't save tool calls to memory
  • Solution: Every interaction (human messages, AI responses, tool calls, tool results) is properly saved

2. Modern AI SDK

  • Problem: Uses deprecated LangChain patterns
  • Solution: Built on Vercel AI SDK for better performance and reliability

3. Simplified Configuration

  • Problem: Complex agent type selection with lots of conditional logic
  • Solution: Single, powerful agent that adapts to your needs

Usage

Basic Setup

  1. Add the node to your workflow
  2. Connect a Language Model (OpenAI, Anthropic, etc.)
  3. Optionally connect:
    • Memory node for conversation persistence
    • Tool nodes for enhanced capabilities
    • Output Parser for structured responses

Input Sources

Choose how to provide the user prompt:

  • Connected Chat Trigger Node: Automatically uses chatInput from chat triggers
  • Define below: Use expressions or static text

Configuration Options

  • System Message: Define the agent's behavior and personality
  • Max Tool Calls: Limit the number of tool interaction rounds
  • Intermediate Webhook URL: Send each partial reply/tool-call to an external workflow in real-time
  • Verbose Logs: Enable/disable detailed console logging
  • Temperature: Control response creativity (0.0 = deterministic, 1.0 = creative)
  • Max Tokens: Set response length limits

Example Workflow

Chat Trigger → Better AI Agent → Response
              ↗ OpenAI Model
              ↗ Buffer Memory
              ↗ Calculator Tool
              ↗ Web Search Tool

Technical Details

Tool Call Memory

Unlike the original agent, this node ensures that all tool interactions are preserved in memory:

User: "What's 25 * 47 and then search for that number"
Assistant: [calls calculator tool]
Tool: "1175"
Assistant: [calls web search tool with "1175"]
Tool: [search results]
Assistant: "The result is 1175. Here's what I found about it..."

All of these interactions are saved to memory for future reference.

AI SDK Integration

Uses modern patterns from Vercel AI SDK:

  • Built-in tool calling support
  • Automatic conversation management
  • Better error handling
  • Real-time step streaming via onStepFinish

Known Limitations

Limitation Work-around
n8n UI does not highlight the attached model or tool nodes because only the Agent executes code Rely on the Agent output or streamed webhook messages for visibility
Tool nodes without an explicit Zod/JSON schema (e.g. raw HTTP Request) may receive incorrect argument keys Wrap such tools in a Custom Code Tool and define a schema, or add few-shot examples
Streaming is step-level, not token-level; the n8n node outputs only when the Agent finishes Use the Intermediate Webhook to push interim messages to a Chat, Slack, etc.
The node's dependencies must be available next to ~/.n8n/custom/BetterAiAgent.node.js Run npm run deploy-local (copies package.json and installs runtime deps)

Development

Building from Source

git clone <repository>
cd better-ai-agent
npm install
npm run build

Testing

npm test

Publishing

npm run package
npm publish

Troubleshooting

Common Issues

  1. "No language model connected": Ensure you've connected a language model node
  2. Tool calls not working: Verify your tools are properly configured and connected
  3. Memory not persisting: Check that your memory node is correctly connected

Debug Information

The node outputs additional debug information:

  • usage: Token usage statistics
  • finishReason: Why the generation stopped
  • toolCalls: List of tools that were called
  • toolResults: Results from tool executions

Contributing

We welcome contributions! Please see our contributing guidelines for more information.

License

MIT License - see LICENSE file for details.

Support

  • Create an issue for bugs or feature requests
  • Join the n8n community for general support
  • Check the documentation for detailed usage examples

Discussion