neo4j-latest

n8n community node for Neo4j — vector search, graph DB, AI tool integration. Fixed version with no internal langchain dependency.

Package Information

Downloads: 88 weekly / 88 monthly
Latest Version: 1.0.0
Author: Vairamuthu R

Available Nodes

Neo4j icon
Neo4j
Run Cypher queries, manage graph data, and perform vector similarity search in Neo4j

Documentation

n8n-nodes-neo4j-fixed

A fixed and fully-featured n8n community node for Neo4j — the leading graph database.

This is a clean rewrite of n8n-nodes-neo4j-extended that fixes the logWrapper import error caused by internal @n8n/n8n-nodes-langchain subpath imports. This package uses only the public n8n-workflow API and the official neo4j-driver.

Features

Feature Details
🗄️ Graph DB Execute Cypher, Create/Update/Delete nodes, Create relationships, Get schema
🔍 Vector Store Similarity search, hybrid search, add texts, add documents, delete by ID
🤖 AI Tool Connects to LangChain agents via the Embedding sub-input
🚀 Auto-Index Automatically creates vector indexes when missing
🔒 Security Input validation prevents Cypher injection
📋 Dynamic Dropdowns Lists existing vector indexes

Installation

In n8n → Settings → Community Nodes → Install:

n8n-nodes-neo4j-fixed

Or via npm:

npm install n8n-nodes-neo4j-fixed

Why This Fix Works

The original n8n-nodes-neo4j-extended imported:

import { logWrapper } from '@n8n/n8n-nodes-langchain/dist/utils/logWrapper';

This is an internal path that newer versions of @n8n/n8n-nodes-langchain removed from their exports map, causing the load failure.

This package achieves the same AI embedding integration using only the public NodeConnectionType.AiEmbedding and getInputConnectionData() API from n8n-workflow.

Credentials

Field Description Default
Connection URI Neo4j connection string neo4j://localhost:7687
Username Database username neo4j
Password Database password —
Database Database name neo4j

Supports neo4j://, bolt://, neo4j+s://, bolt+s:// protocols.

Operations

Graph Database

  • Execute Query — Run any Cypher query with optional parameters
  • Create Node — Create a node with label and properties
  • Update Node — Update properties of an existing node by match key
  • Delete Node — Detach-delete a node by match key
  • Create Relationship — Create a relationship between two nodes
  • Get Schema — Retrieve labels, relationship types, and property keys

Vector Store

Requires an Embedding model connected to the Embedding sub-input

  • Similarity Search — Vector (cosine) or Hybrid (vector + fulltext) search
  • Add Texts — Embed and store plain text strings
  • Add Documents — Embed and store { pageContent, metadata } objects
  • Delete by ID — Remove vectors by their element ID

Index Management

  • List Indexes — Show all vector indexes in the database
  • Create Index — Create a vector index with dimension and similarity function
  • Delete Index — Drop a vector index
  • Get Index Info — Get details about a specific index

Vector Dimensions

Neo4j supports dimensions 1–2048.

Model Dimension
OpenAI text-embedding-ada-002 1536
OpenAI text-embedding-3-small 1536
sentence-transformers/all-MiniLM-L6-v2 384
sentence-transformers/all-mpnet-base-v2 768
Cohere Embed v3 1024
GigaChat Embeddings 2048

Note: OpenAI text-embedding-3-large (3072D) exceeds Neo4j's limit. Use text-embedding-3-small instead or reduce dimensions.

Security

  • Identifier validation: ^[a-zA-Z_$][a-zA-Z0-9_$]*$
  • 255-character limit on all identifier fields
  • Parameterized queries for all user-supplied values
  • No eval or dynamic code execution

Compatibility

  • n8n ≥ 1.0.0
  • Neo4j ≥ 4.4 (5.x recommended for full vector support)
  • Node.js ≥ 18

License

MIT

Discussion