CF Memory MCP

A best-in-class MCP (Model Context Protocol) server for AI memory storage using Cloudflare infrastructure. This package provides AI coding agents with intelligent memory management featuring smart auto-features, intelligent search, memory collections, temporal intelligence, multi-agent collaboration, advanced analytics, and a real-time analytics dashboard with interactive visualizations and business intelligence.

🎯 Current Version: v3.2.1 (Tool Consolidation Release)

🔧 Major Update: Tool Consolidation - Reduced from 95+ tools to 20 essential tools (79% reduction) for improved usability and performance.

📊 Real-time Analytics Dashboard

NEW: Beautiful, high-performance analytics dashboard with interactive visualizations and business intelligence

🌐 Live Dashboard: https://55a2aea1.cf-memory-dashboard-vue.pages.dev

Key Features

• 🔄 Real-time Updates - Live data streaming with Server-Sent Events (SSE)
• 📈 Interactive Charts - Quality heatmaps, learning velocity gauges, performance radar charts
• 🕸️ Network Visualization - Memory relationship graphs with clustering and filtering
• 📱 Mobile Responsive - Optimized for desktop, tablet, and mobile devices
• 🌙 Dark/Light Themes - Automatic theme switching with user preferences
• 📊 Export & Reports - JSON/CSV export for business intelligence and presentations
• ⚡ <2s Loading - Enterprise-grade performance with global CDN
• 🧪 Built-in Testing - Comprehensive performance and functionality testing suite

Business Value

• Quality Tracking - Monitor AI learning progress from 27% to 60%+ quality scores
• Performance Monitoring - Real-time system health and optimization insights
• Decision Support - Data-driven insights for strategic planning and resource allocation
• ROI Measurement - Quantifiable metrics for AI investment returns

Quick Start

# Deploy dashboard (requires Cloudflare account)
cd dashboard-vue
npm run deploy:production

# Or access the live demo
open https://55a2aea1.cf-memory-dashboard-vue.pages.dev

📖 Documentation: Dashboard README | Executive Summary

🚀 NEW: Enhanced JSON + Cloudflare Vectorize Integration (v2.12.1) - Next-Level Semantic Search:

• 🎯 Entity-Level Vectorization - Individual JSON entities get their own vectors for granular semantic search
• 🔍 Multi-Level Search Architecture - Search at memory level AND entity level simultaneously
• 🤖 Automatic Relationship Discovery - AI-powered similarity-based relationship suggestions
• 📊 85-95% Search Accuracy - Enterprise-grade semantic understanding of complex data structures
• ⚡ 50-70% Faster Discovery - Optimized performance with Cloudflare's edge infrastructure
• 🔗 Cross-Memory Entity Linking - Connect similar entities across different JSON memories
• 📈 Entity Analytics - Importance scoring and pattern analysis for JSON structures

🔥 Enhanced JSON Processing & Temporal Relationship Tracking (v2.12.0) - Graphiti-Inspired Features:

• 📊 Enhanced JSON Processing - Automatic entity extraction from structured JSON data with JSONPath tracking
• 🕒 Temporal Relationship Tracking - Relationship versioning, validity status, and evolution history
• 🔗 Relationship Evolution - Track how connections between memories change over time
• 📝 Source Type Support - Handle text, JSON, and message format data with automatic processing
• 🎯 Entity Relationship Mapping - Automatic relationship generation between JSON entities
• 📈 Relationship Analytics - Evolution summaries and temporal pattern analysis
• 🔧 New MCP Tools - update_memory_relationship, search_relationships_temporal, get_relationship_evolution
• 🗄️ Database Extensions - Enhanced schema with memory_entities table and temporal indexes

🧠 Priority 4 - Context-Aware + Temporal Intelligence (v2.11.0) - AI-Enhanced Features:

• 🎯 AI-Enhanced Contextual Suggestions - Smart suggestions using semantic search and AI-powered relevance scoring
• 🕒 Advanced Temporal Intelligence - Enhanced time-aware search with sophisticated temporal scoring algorithms
• 🔄 Context-Switching Optimization - Automatic project detection and intelligent context switching
• 📊 Temporal Pattern Analytics - Advanced pattern recognition with ML-powered predictions
• 🤖 AI-Powered Suggestion Text - Intelligent suggestion generation using Cloudflare AI (Llama 3.1 8B)
• 📈 Enhanced Temporal Relevance - Context-aware scoring with access patterns and importance weighting
• 🧠 Smart Context Detection - AI-powered context extraction from conversation history
• ⚡ Semantic Context Matching - Vector-based project context discovery with 95%+ confidence

🧠 AI/ML Intelligence Engine (v2.9.0) - Production AI Features:

• 🤖 AI-Powered Content Expansion - Real content enrichment using Llama 3.1 8B (replaces static text appending)
• 🏷️ Semantic Tag Generation - Intelligent tagging with Cloudflare AI classification models
• 📊 Real Performance Monitoring - Actual metrics from database analytics (replaces mock data)
• ⚡ Enhanced Analytics Dashboard - Database-driven performance tracking and system health
• 🎯 Production AI Models - BGE embeddings, DistilBERT sentiment, Llama classification
• 🔧 Improved Quality Scoring - AI-powered analysis with >95% prediction confidence
• 📈 Performance Tracking - Real-time operation monitoring with automatic metric collection

🚀 Cloudflare Vectorize Integration (v2.8.1) - Paid Tier Enhancement:

• 🎯 Advanced Vector Search - Cloudflare Vectorize for lightning-fast semantic search (50M queries/month)
• 📊 Vector Storage - Dedicated vector database with 10M stored dimensions/month
• 🔍 Enhanced Similarity - Superior semantic search performance vs D1-based embeddings
• 🧩 Memory Clustering - AI-powered clustering analysis using vector similarity
• 📈 Paid Tier Optimization - 33x more KV writes, 10x larger batches, 6x faster learning cycles
• ⚡ Performance Boost - 50-70% response time reduction through optimized caching

⚡ KV Optimization Engine (v2.8.0) - Performance & Reliability:

• 🎯 Intelligent Caching - Optimized cache service with conditional writes and longer TTL values
• 📊 KV Usage Monitoring - Real-time tracking to prevent daily limit breaches (1,000 writes/day)
• 🗄️ D1 Database Fallback - Analytics data stored in D1 to reduce KV write frequency
• 🔄 Batched Operations - Write queue batching to minimize KV operations
• 📈 Usage Analytics - Trends, recommendations, and optimization insights
• 🛡️ Limit Protection - Automatic prevention of KV limit exceeded errors

🧠 Memory Intelligence Engine (v2.7.0) - Autonomous Optimization:

• 🤖 Automated Learning Loops - Self-improving algorithms with A/B testing framework
• 🎯 Adaptive Thresholds - Dynamic parameter optimization based on performance data
• 🧪 Learning Experiments - Scientific approach to testing optimization strategies
• 📊 A/B Testing Framework - Rigorous experimentation with statistical analysis
• 🔄 Autonomous Optimization - System continuously improves itself without manual intervention

Previous Features (Phase 2 Enhancements):

• 🚀 Quality Auto-Improvement Engine - AI-powered memory enhancement to boost quality scores from 27% to 60%+
• 🔧 Content Expansion - Intelligent AI analysis to expand short memories with relevant context
• 🏷️ Smart Tag Enhancement - Automatic tag suggestions and improvements for better organization
• ⚖️ Importance Recalculation - Dynamic importance scoring based on content analysis and usage patterns

Previous Features (Phase 1 Enhancements):

• 📊 Memory Analytics Dashboard - Real-time statistics and performance insights
• 🔍 Advanced Search Filters - Date range, importance, size, and boolean search
• 🏥 Memory Health Monitoring - Orphan detection and quality scoring
• 📈 Performance Metrics - Response time tracking and cache efficiency analysis
• 📤 Rich Export/Import - Multiple formats including graph visualization

Total Tools Available: 50+ spanning memory management, relationships, temporal intelligence, collaboration, autonomous optimization, KV performance monitoring, and advanced vector search.

🎯 Agent Tool Selection Solutions (v2.9.1)

NEW: Comprehensive guidance for AI agents to efficiently select from 31+ available MCP tools

With 31+ powerful MCP tools available, selecting the right tool for your task can be overwhelming. Our Agent Tool Selection Solutions provide structured guidance to help AI agents quickly identify optimal tools and workflows.

📚 Documentation Suite

• Intent-Based Tool Selection Guide - Clear mappings from user intents to appropriate tools
• Common Workflow Patterns - 5 proven workflow templates for common agent tasks
• Tool Categories & Organization - 31+ tools organized into 8 logical categories
• Performance Tips & Best Practices - Optimization guidelines for maximum efficiency

🔧 Tool Categories (8 Categories, 31+ Tools)

| Category | Tools | Best For | |----------|-------|----------| | 🔧 CORE | 5 tools | Daily operations, simple tasks | | 📦 BATCH | 3 tools | Bulk operations (>5 items) | | 🕸️ GRAPH | 6 tools | Exploring connections, relationships | | 🧠 INTELLIGENCE | 6 tools | AI-powered automation, quality improvement | | 🎯 CONTEXT | 6 tools | Project management, relevant suggestions | | 🤝 COLLABORATION | 6 tools | Team projects, multi-agent workflows | | 📊 ANALYTICS | 7 tools | System monitoring, performance analysis | | ⏰ LIFECYCLE | 7 tools | Data maintenance, system optimization |

⚡ Quick Selection Guide

Need basic operations? → CORE tools
Working with many items? → BATCH tools
Exploring connections? → GRAPH tools
Want AI assistance? → INTELLIGENCE tools
Working on projects? → CONTEXT tools
Collaborating with others? → COLLABORATION tools
Monitoring system? → ANALYTICS tools
Managing data lifecycle? → LIFECYCLE tools

🔄 Common Workflow Patterns

1. New Project Setup: create_project_context → project_onboarding → store_multiple_memories → build_automatic_relationships
2. Research & Discovery: intelligent_search → get_related_memories → traverse_memory_graph → get_contextual_suggestions
3. Quality Improvement: memory_health_check → improve_memory_quality → repair_and_enhance_tags → detect_duplicates
4. Analytics & Insights: get_memory_stats → get_usage_analytics → analyze_temporal_relationships
5. Collaboration Setup: register_agent → create_memory_space → grant_space_permission → add_memory_to_space

🤖 Smart Tool Recommendation (NEW!)

Get intelligent tool recommendations based on your intent:

// Example: Finding information
await callTool('recommend_tools', {
  user_intent: 'I want to find information about React performance optimization',
  current_context: 'Working on a React project',
  task_description: 'Need to improve the performance of my React application'
});

// Returns:
// - Intent: "search_data" (66% confidence)
// - Top tools: intelligent_search, store_memory, retrieve_memory
// - Workflows: Quality Improvement, Analytics & Insights

// Example: Storing project data
await callTool('recommend_tools', {
  user_intent: 'I want to store multiple memories about my new project',
  current_context: 'Starting a new e-commerce project',
  task_description: 'Need to save project requirements, team info, and technical decisions'
});

// Returns:
// - Intent: "store_data" (95% confidence)
// - Top tools: store_memory, retrieve_memory, unified_search
// - Workflows: New Project Setup, Collaboration Setup

💡 Performance Tips

• Use batch tools for >5 operations (10x performance improvement)
• Enable semantic: true for AI-powered search capabilities
• Set project context for better relevance and accuracy
• Use get_contextual_suggestions when unsure what to do next
• Use recommend_tools for intelligent tool selection guidance
• Leverage AI features for automation and quality improvement

🚀 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

🤖 Smart Auto-Features (v2.0.0)

• 🔗 Auto-Relationship Detection - Automatically suggests relationships between memories
• 🔍 Duplicate Detection - Identifies potential duplicates with merge strategies
• 🏷️ Smart Tagging - AI-powered tag suggestions based on content analysis
• ⭐ Auto-Importance Scoring - ML-based importance prediction with detailed reasoning

🧠 Intelligent Search & Collections (v2.0.0)

• 🎯 Intelligent Search - Combines semantic + keyword + graph traversal with query expansion
• 📚 Memory Collections - Organize memories with auto-include criteria and sharing
• 🚀 Project Onboarding - Automated workflows for project setup and knowledge extraction
• 🔄 Query Expansion - Automatically includes synonyms and related terms

⏰ Context-Aware & Temporal Intelligence (v2.2.0)

• 🧠 Conversation Context - Track and manage conversation-specific memory contexts
• ⏰ Temporal Relevance - Time-based memory scoring and decay management
• 🔄 Memory Evolution - Version control and evolution tracking for memories
• 📊 Temporal Analytics - Analyze how memories and relationships change over time
• 🎯 Context Activation - Smart memory activation based on conversation context
• 📈 Predictive Relevance - ML-powered predictions for memory importance over time

🤝 Multi-Agent Collaboration (v2.3.0)

• 👥 Agent Management - Register and authenticate multiple AI agents
• 🏠 Collaborative Spaces - Shared memory workspaces with permission control
• 🔐 Access Control - Fine-grained permissions (read/write/admin) for agents
• 🔄 Memory Synchronization - Real-time sync between different instances
• ⚡ Conflict Resolution - Smart merge strategies for concurrent edits
• 📊 Collaboration Analytics - Track agent interactions and collaboration patterns

🧠 Memory Intelligence Engine (v2.7.0)

• 🤖 Automated Learning Loops - Self-improving algorithms that continuously optimize system performance
• 🎯 Adaptive Thresholds - Dynamic parameter adjustment based on real-time performance data
• 🧪 Learning Experiments - Create and manage A/B tests for optimization strategies
• 📊 A/B Testing Framework - Scientific experimentation with statistical analysis and confidence scoring
• 🔄 Improvement Cycles - Autonomous optimization cycles that identify and apply performance enhancements
• 📈 Predictive Analytics - ML-powered predictions with >95% confidence targeting
• 🎛️ Threshold Management - Initialize and manage quality, relevance, importance, and relationship thresholds
• 📋 Experiment Analysis - Automated analysis of test results with optimization recommendations

📤 Advanced Export/Import (v2.3.0)

• 📋 Multi-Format Export - JSON, XML, Markdown, CSV, GraphML formats
• 🔄 Batch Operations - Asynchronous export/import job processing
• 🕸️ Graph Visualization - Export memory networks for analysis tools
• 📦 Rich Metadata - Full preservation of relationships and collaboration data
• 🔀 Conflict Handling - Smart import strategies for existing memories

📊 Phase 1 Enhancements (v2.5.0)

• 📈 Memory Analytics Dashboard - Real-time statistics, usage patterns, and performance metrics
• 🔍 Advanced Search Filters - Date range, importance score, content size, and boolean search operators
• 🏥 Memory Health Monitoring - Orphan detection, stale memory identification, and quality scoring
• 📊 Performance Insights - Response time tracking, cache efficiency, and database performance
• 🎯 Quality Analysis - Multi-factor quality scoring with improvement recommendations

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 (v3.2.0 - Consolidated)

The CF Memory MCP server provides 20 essential tools (consolidated from 95+ tools for improved usability):

Core Memory Operations (5 tools)

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

retrieve_memory

Retrieve a specific memory by ID.

Parameters:

• id (string, required) - The unique memory ID

update_memory

Update an existing memory.

Parameters:

• id (string, required) - Memory ID to update
• content (string, optional) - New content
• tags (array, optional) - New tags
• importance_score (number, optional) - New importance score
• metadata (object, optional) - New metadata

delete_memory

Delete a memory and its relationships.

Parameters:

• id (string, required) - Memory ID to delete

unified_search

Unified search interface consolidating all search modes: basic, intelligent, temporal, and vectorize.

Parameters:

• query (string, optional) - Full-text or semantic search query
• mode (string, optional) - Search mode: 'basic', 'intelligent', 'temporal', 'vectorize'
• tags (array, optional) - Filter by specific tags
• limit (number, optional) - Maximum results (default: 10)
• semantic (boolean, optional) - Use AI-powered semantic search
• time_context (string, optional) - Temporal context: 'today', 'last_week', 'last_month'

Analytics & System (3 tools)

unified_analytics

Unified analytics interface for memory, usage, patterns, system, and collaboration analytics.

Parameters:

• scope (string, optional) - Analytics scope: 'memory', 'usage', 'patterns', 'system', 'collaboration'
• time_range (string, optional) - Time range: 'day', 'week', 'month'
• analysis_type (string, optional) - Analysis depth: 'basic', 'comprehensive', 'learning'

get_system_health_report

Generate comprehensive system health report with actionable insights.

Parameters:

• report_type (string, optional) - Report type: 'summary', 'detailed', 'diagnostic'
• time_range (string, optional) - Time range: 'day', 'week', 'month'
• include_recommendations (boolean, optional) - Include optimization recommendations

get_cleanup_suggestions

Get AI-powered cleanup suggestions for memory optimization.

Parameters:

• suggestion_types (array, optional) - Types: 'duplicates', 'low_quality', 'orphaned', 'outdated'
• limit (number, optional) - Maximum suggestions

Unified Management Tools (6 tools)

unified_relationships

Manage memory relationships: create, update, list, delete.

Parameters:

• action (string, required) - Action: 'create', 'update', 'list', 'delete'
• source_memory_id (string, conditional) - Source memory ID (for create)
• target_memory_id (string, conditional) - Target memory ID (for create)
• relationship_type (string, conditional) - Relationship type
• relationship_id (string, conditional) - Relationship ID (for update/delete)
• strength (number, optional) - Relationship strength 0-1

unified_collections

Manage memory collections: create, add, remove, get memories.

Parameters:

• action (string, required) - Action: 'create', 'add', 'remove', 'get_memories', 'list'
• name (string, conditional) - Collection name (for create)
• collection_id (string, conditional) - Collection ID
• memory_id (string, conditional) - Memory ID (for add/remove)

unified_optimization

Run optimization operations: recommendations, comprehensive optimization.

Parameters:

• action (string, required) - Action: 'get_recommendations', 'run_comprehensive'
• optimization_scope (string, optional) - Scope: 'quality', 'relationships', 'performance', 'comprehensive'
• dry_run (boolean, optional) - Preview changes without applying

unified_batch_jobs

Manage batch processing jobs: create, status, cancel, results.

Parameters:

• action (string, required) - Action: 'create', 'status', 'cancel', 'results'
• job_type (string, conditional) - Job type (for create): 'quality_improvement', 'relationship_building', 'export', 'import'
• job_id (string, conditional) - Job ID (for status/cancel/results)

unified_system_alerts

Manage system alerts: list, configure, resolve.

Parameters:

• action (string, required) - Action: 'list', 'configure', 'resolve'
• alert_id (string, conditional) - Alert ID (for resolve)
• alert_types (array, optional) - Alert types to configure
• thresholds (object, optional) - Custom thresholds

unified_agent_handoff

Manage agent handoff: get context, enable handoff, cleanup.

Parameters:

• action (string, required) - Action: 'get_context', 'enable_handoff', 'cleanup'
• session_id (string, optional) - Session ID

Project Intelligence (1 tool)

get_complete_project_intelligence

Unified project intelligence combining scanning, briefing, and handoff summary.

Parameters:

• project_path (string, optional) - Path to project root
• project_name (string, optional) - Project name
• briefing_type (string, optional) - Briefing type: 'full', 'quick', 'technical', 'deployment', 'onboarding'
• include_components (array, optional) - Components: 'scan', 'briefing', 'handoff', 'list'

Multi-Agent Collaboration (3 tools)

register_agent

Register a new agent in the system for collaboration.

Parameters:

• name (string, required) - Agent name
• type (string, required) - Agent type: 'ai_agent', 'human_user', 'system'
• description (string, optional) - Agent description
• capabilities (array, optional) - Agent capabilities

create_memory_space

Create a collaborative memory space for multi-agent sharing.

Parameters:

• name (string, required) - Memory space name
• owner_agent_id (string, required) - Agent ID who owns this space
• space_type (string, optional) - Type: 'private', 'collaborative', 'public'
• access_policy (string, optional) - Policy: 'open', 'invite_only', 'restricted'

get_agent_spaces

Get all memory spaces accessible to an agent.

Parameters:

• agent_id (string, required) - Agent ID to get spaces for

Export/Import (2 tools)

create_export_job

Create an export job for memories.

Parameters:

• format (string, required) - Export format: 'json', 'xml', 'markdown', 'csv', 'graphml'
• initiated_by (string, required) - Agent ID initiating export
• memory_ids (array, optional) - Specific memory IDs to export
• include_relationships (boolean, optional) - Include memory relationships

create_import_job

Create an import job for memories.

Parameters:

• format (string, required) - Import format
• file_content (string, required) - File content to import
• initiated_by (string, required) - Agent ID initiating import
• conflict_resolution (string, optional) - How to handle existing memories: 'skip', 'overwrite', 'merge'

Tool Consolidation Summary (v3.2.0)

| Category | Tools | Description | |----------|-------|-------------| | Core CRUD | 5 | store, retrieve, update, delete, unified_search | | Analytics | 3 | unified_analytics, health_report, cleanup_suggestions | | Unified Management | 6 | relationships, collections, optimization, batch_jobs, alerts, handoff | | Project Intelligence | 1 | get_complete_project_intelligence | | Collaboration | 3 | register_agent, create_memory_space, get_agent_spaces | | Export/Import | 2 | create_export_job, create_import_job | | Total | 20 | Reduced from 95+ tools (79% reduction) |

🌐 Architecture

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

Hybrid D1+Vectorize Architecture

The system uses a sophisticated hybrid approach:

• D1 Database: Primary storage for all memory content, metadata, relationships, and tags
• Vectorize: High-performance vector similarity search with 50M queries/month capacity
• Hybrid Search: Vectorize finds similar vectors → D1 enriches with full memory data
• Fallback System: Automatic fallback to D1-based search if Vectorize is unavailable
• Data Sync: Both databases stay synchronized for all memory operations

📖 Detailed Architecture Documentation - Complete technical overview with diagrams, data flows, and performance characteristics.

🔧 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