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Memara

Last updated Aug 3, 2025

n8n community node for Memara memory system - Store and retrieve memories with semantic search in your workflows

5 Weekly Downloads
40 Monthly Downloads

Included Nodes

Memara

Description

Memara n8n Community Node

Memara Logo

A powerful n8n community node that integrates Memara's semantic memory system into your workflows. Store, search, and retrieve memories with AI-powered semantic search capabilities.

๐Ÿš€ Features

  • Semantic Memory Storage: Store information with intelligent context understanding
  • AI-Powered Search: Find relevant memories using natural language queries
  • Memory Spaces: Organize memories in isolated spaces for different projects
  • CRUD Operations: Complete create, read, update, delete functionality
  • API Integration: Direct integration with Memara's production API
  • Easy Configuration: Simple API key authentication setup

๐Ÿ“ฆ Installation

Option 1: n8n Community Node Installation (Recommended)

  1. In your n8n instance, go to Settings โ†’ Community Nodes
  2. Enter the package name: n8n-nodes-memara
  3. Click Install

Option 2: Manual Installation

# Using npm
npm install n8n-nodes-memara

# Using yarn
yarn add n8n-nodes-memara

Option 3: Development Installation

# Clone and install locally
git clone https://github.com/memara-ai/n8n-nodes-memara.git
cd n8n-nodes-memara
npm install
npm run build
npm link

# Link to your n8n installation
cd ~/.n8n/nodes
npm link n8n-nodes-memara

๐Ÿ”ง Configuration

1. Get Your Memara API Key

  1. Visit Memara Dashboard
  2. Go to Settings โ†’ API Keys
  3. Create a new API key
  4. Copy the key (format: mk_live_...)

2. Configure Credentials in n8n

  1. In n8n, create a new Memara API credential
  2. Enter your API key
  3. (Optional) Set a default Space ID
  4. Test the connection

3. Add Memara Node to Workflow

  1. In your workflow, click Add Node
  2. Search for "Memara"
  3. Select the Memara node
  4. Choose your configured credentials

๐Ÿ“ Usage Examples

Basic Memory Creation

{
  "resource": "memory",
  "operation": "create",
  "content": "Customer John Smith reported billing issue with invoice #12345. Resolved by applying 10% discount due to delayed delivery.",
  "title": "Customer Issue Resolution",
  "tags": "customer-service, billing, discount"
}

Semantic Memory Search

{
  "resource": "memory",
  "operation": "search",
  "query": "billing problems with customers",
  "limit": 5
}

Memory Space Management

{
  "resource": "space",
  "operation": "create",
  "name": "Customer Support",
  "description": "Knowledge base for customer support team"
}

๐ŸŽฏ Common Workflow Patterns

1. Customer Support Knowledge Base

1. HTTP Request โ†’ Fetch support ticket
2. Memara โ†’ Search for similar issues
3. Memara โ†’ Create memory of resolution
4. Email โ†’ Send response to customer

2. Content Creation Assistant

1. Webhook โ†’ Receive content request
2. Memara โ†’ Search for related content
3. Code โ†’ Generate new content using context
4. Memara โ†’ Store new content as memory

3. Lead Qualification System

1. Form โ†’ Capture lead information
2. Memara โ†’ Search for similar leads
3. Memara โ†’ Store lead profile
4. Slack โ†’ Alert sales team with context

๐Ÿ” Available Operations

Memory Operations

Operation Description Required Parameters
Create Store new memory content
Search Find relevant memories query
Update Modify existing memory memoryId, content
Delete Remove memory memoryId
List Get all memories None

Space Operations

Operation Description Required Parameters
List Get all spaces None
Create Create new space name

โš™๏ธ Parameters Reference

Memory Parameters

  • Content (required): The main content/information to store
  • Title (optional): Short title for the memory
  • Tags (optional): Comma-separated tags for organization
  • Space ID (optional): Target space (uses default if not specified)
  • Memory ID (required for update/delete): Unique memory identifier

Search Parameters

  • Query (required): Natural language search query
  • Limit (optional): Maximum results to return (1-100, default: 10)
  • Space ID (optional): Search within specific space

Space Parameters

  • Name (required): Space name
  • Description (optional): Space description

๐Ÿ› Troubleshooting

Common Issues

"Invalid API Key" Error

  • Verify your API key is correct and starts with mk_live_
  • Check that the key hasn't expired in your Memara dashboard
  • Ensure you're using the production API URL: https://api.memara.io

"Space Not Found" Error

  • Verify the Space ID exists in your Memara account
  • Check if you have access to the specified space
  • Use the List Spaces operation to see available spaces

Node Not Appearing in n8n

  • Restart n8n after installation
  • Check that the package installed correctly: npm list n8n-nodes-memara
  • Verify n8n version compatibility (requires n8n 1.0+)

Getting Help

๐Ÿงช Development

Local Development Setup

# Clone the repository
git clone https://github.com/memara-ai/n8n-nodes-memara.git
cd n8n-nodes-memara

# Start development environment
./scripts/docker-n8n.sh start

# Access environments
# Development: http://localhost:5678 (admin/admin)
# Testing: http://localhost:5679 (admin/admin)

Available Scripts

# Build the node
./scripts/docker-n8n.sh build

# Run linter
./scripts/docker-n8n.sh lint

# View logs
./scripts/docker-n8n.sh logs

# Execute commands in container
./scripts/docker-n8n.sh exec npm test

๐Ÿ“„ License

MIT License – see LICENSE.md for details

๐Ÿค Contributing

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes
  4. Add tests if applicable
  5. Submit a pull request

๐Ÿ“ž Support


Made with โค๏ธ by the Memara Team