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cf-memory-mcp
cf-memory-mcp/bin/cf-memory-mcp.js

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Readme

CF Memory MCP

A portable MCP (Model Context Protocol) server for AI memory storage using Cloudflare infrastructure. This package allows AI coding agents to store, retrieve, and search memories using a production-ready, serverless backend with semantic search, batch operations, and graph traversal capabilities.

🚀 Quick Start

# Run directly with npx (no installation required)
npx cf-memory-mcp

# Or install globally
npm install -g cf-memory-mcp
cf-memory-mcp

✨ Features

Core Features

🌐 Completely Portable - No local setup required, connects to deployed Cloudflare Worker
⚡ Production Ready - Uses Cloudflare D1 database and KV storage for reliability
🔧 Zero Configuration - Works out of the box with any MCP client
🌍 Cross Platform - Supports Windows, macOS, and Linux
📦 NPX Compatible - Run instantly without installation
🔒 Secure - Built on Cloudflare's secure infrastructure
🚄 Fast - Global edge deployment with KV caching

Advanced Features

🧠 Semantic Search - AI-powered vector search using Cloudflare AI Workers
🕸️ Knowledge Graph - Store and traverse relationships between memories
📦 Batch Operations - Efficiently process multiple memories at once
🔍 Graph Traversal - Find paths and connections between related memories
🎯 Smart Filtering - Advanced search with tags, importance, and similarity

🛠️ Usage

With MCP Clients

Add to your MCP client configuration:

{
  "mcpServers": {
    "cf-memory": {
      "command": "npx",
      "args": ["cf-memory-mcp"]
    }
  }
}

With Augment

Add to your augment-config.json:

{
  "mcpServers": {
    "cf-memory": {
      "command": "npx",
      "args": ["cf-memory-mcp"]
    }
  }
}

With Claude Desktop

Add to your Claude Desktop MCP configuration:

{
  "mcpServers": {
    "cf-memory": {
      "command": "npx",
      "args": ["cf-memory-mcp"]
    }
  }
}

🔧 Available Tools

The CF Memory MCP server provides comprehensive memory management tools:

Core Memory Operations

`store_memory`

Store a new memory with optional metadata and tags.

Parameters:

content (string, required) - The memory content
tags (array, optional) - Tags for categorization
importance_score (number, optional) - Importance score 0-10
metadata (object, optional) - Additional metadata

`search_memories`

Search memories by content and tags with optional semantic search.

Parameters:

query (string, optional) - Full-text or semantic search query
tags (array, optional) - Filter by specific tags
limit (number, optional) - Maximum results (default: 10)
offset (number, optional) - Results offset (default: 0)
min_importance (number, optional) - Minimum importance score
semantic (boolean, optional) - Use AI-powered semantic search
similarity_threshold (number, optional) - Minimum similarity for semantic search

`retrieve_memory`

Retrieve a specific memory by ID.

Parameters:

id (string, required) - The unique memory ID

Batch Operations

`store_multiple_memories`

Store multiple memories in a single batch operation.

Parameters:

memories (array, required) - Array of memory objects to store

`update_multiple_memories`

Update multiple memories in a single batch operation.

Parameters:

updates (array, required) - Array of memory updates with ID and data

`search_and_update`

Search for memories and update them in one operation.

Parameters:

search (object, required) - Search criteria
update (object, required) - Update data to apply

Graph & Relationship Operations

`traverse_memory_graph`

Traverse the memory graph from a starting point to find connected memories.

Parameters:

start_memory_id (string, required) - Starting memory ID
relationship_types (array, optional) - Filter by relationship types
max_depth (number, optional) - Maximum traversal depth (default: 3)
direction (string, optional) - Direction: 'outgoing', 'incoming', or 'both'
min_strength (number, optional) - Minimum relationship strength

`find_memory_path`

Find a path between two memories through relationships.

Parameters:

start_memory_id (string, required) - Starting memory ID
end_memory_id (string, required) - Target memory ID
relationship_types (array, optional) - Filter by relationship types
max_depth (number, optional) - Maximum path length (default: 5)
min_strength (number, optional) - Minimum relationship strength

`get_related_memories`

Get memories related to a specific memory with various options.

Parameters:

memory_id (string, required) - Memory ID to find related memories for
relationship_types (array, optional) - Filter by relationship types
min_strength (number, optional) - Minimum relationship strength
limit (number, optional) - Maximum results (default: 10)
include_indirect (boolean, optional) - Include indirectly related memories
max_hops (number, optional) - Maximum hops for indirect relationships

🌐 Architecture

┌─────────────────┐    ┌──────────────────┐    ┌─────────────────────┐
│   MCP Client    │    │  cf-memory-mcp   │    │  Cloudflare Worker  │
│   (Augment,     │◄──►│   (npm package)  │◄──►│   (Production API)  │
│   Claude, etc.) │    │                  │    │                     │
└─────────────────┘    └──────────────────┘    └─────────────────────┘
                                                          │
                                                          ▼
                                               ┌─────────────────────┐
                                               │  Cloudflare D1 DB   │
                                               │  + KV Storage       │
                                               └─────────────────────┘

🔧 Command Line Options

# Start the MCP server
npx cf-memory-mcp

# Show version
npx cf-memory-mcp --version

# Show help
npx cf-memory-mcp --help

# Enable debug logging
DEBUG=1 npx cf-memory-mcp

🌍 Environment Variables

DEBUG=1 - Enable debug logging
MCP_DEBUG=1 - Enable MCP-specific debug logging

📋 Requirements

Node.js 16.0.0 or higher
Internet connection (connects to Cloudflare Worker)
MCP client (Augment, Claude Desktop, etc.)

🚀 Why CF Memory MCP?

Traditional Approach ❌

Clone repository
Set up local database
Configure environment variables
Manage local server process
Handle updates manually

CF Memory MCP ✅

Run npx cf-memory-mcp
That's it! 🎉

🔒 Privacy & Security

No local data storage - All data stored securely in Cloudflare D1
HTTPS encryption - All communication encrypted in transit
Edge deployment - Data replicated globally for reliability
No API keys required - Public read/write access for simplicity

🤝 Contributing

Contributions are welcome! Please see the GitHub repository for more information.

📄 License

MIT License - see LICENSE file for details.

🔗 Links

GitHub Repository: https://github.com/johnlam90/cf-memory-mcp
npm Package: https://www.npmjs.com/package/cf-memory-mcp
Issues: https://github.com/johnlam90/cf-memory-mcp/issues
MCP Specification: https://modelcontextprotocol.io/

Made with ❤️ by John Lam