What is Cldmemory

MCP Memory Server is a memory system designed to mimic human-like memory types using a Qdrant vector database and OpenAI embeddings. It supports various memory types such as episodic, semantic, procedural, emotional, sensory, and working memory, making it versatile for diverse use cases in memory management.

Use cases

The MCP Memory Server can be utilized for storing personal experiences, facts, procedural knowledge, emotional insights, and sensory impressions. It’s useful in applications that require tracking of user interactions, decisions, and context-based memory retrieval, enhancing user experience through personalized memory management.

How to use

To utilize the MCP Memory Server, first install the necessary dependencies and configure your environment by editing the .env file. Run a local Qdrant instance or connect to an existing one, build the project, and use the MCP tools for memory operations via the Claude Code CLI, following the specified JSON format for all commands.

Key features

Key features of MCP Memory Server include support for different types of memory, automatic project tracking, importance scoring, emotional valence, context integration, and environment metadata for enhanced relevance in memory searches. It also provides an analytics tool for memory analysis and insights.

Where to use

MCP Memory Server can be used in applications requiring sophisticated memory management, such as personal assistants, knowledge management systems, and user behavior analysis tools in sectors like education, customer support, and software development.

MCP Memory Server

A human-like memory system using Qdrant vector database and OpenAI embeddings, accessible through the Model Context Protocol (MCP).

Features

• Human-like Memory Types:

  • Episodic (personal experiences)
  • Semantic (facts and knowledge)
  • Procedural (how to do things)
  • Emotional (emotional memories)
  • Sensory (sensory impressions)
  • Working (short-term memory)

• Memory Characteristics:

  • Importance scoring (0-1)
  • Emotional valence (-1 to 1)
  • Associations between memories
  • Context (location, people, mood, activity)
  • Decay factor and access tracking
  • Automatic project tracking (hostname:folder)
  • Custom metadata via environment variables

Setup

1. Install dependencies:

   npm install
   

2. Configure environment:

   cp .env.example .env
   # Edit .env with your settings
   

   New environment variables:

   • MEMORY_METADATA - Optional metadata to include with all memories
     • Format: "key:value,key2:value2" or just "value" (stored as user:value)
     • Examples: "server:prod,user:john" or "davidstrejc"

3. Start Qdrant (if using local):

   docker run -p 6333:6333 -p 6334:6334 \
     --name qdrant-memory \
     -v $(pwd)/qdrant_storage:/qdrant/storage:z \
     qdrant/qdrant
   

   Note: Qdrant URL supports both HTTP and HTTPS protocols (e.g., https://your-qdrant-instance.com:6333)

4. Build the project:

   npm run build
   

Testing with Claude Code

Use the MCP configuration file with Claude Code CLI:

# Basic usage
claude -p "Store a memory about today's meeting" --mcp-config claude-code-mcp.json

# Skip permissions for automation
claude -p "Search my memories" --mcp-config claude-code-mcp.json --dangerously-skip-permissions

# List available tools
claude -p "List available memory tools" --mcp-config claude-code-mcp.json

Available MCP tools (prefixed with mcp__memory__):

• store_memory - Store a new memory
• search_memories - Search for memories using natural language (returns full details)
• quick_search_memories - Fast search returning only summaries for browsing
• get_memory - Retrieve a specific memory by ID
• update_memory - Update an existing memory
• delete_memory - Delete a memory
• analyze_memories - Analyze memory patterns

Example Usage

IMPORTANT: All MCP tools expect JSON objects as parameters, NOT plain strings.

New Features

Automatic Project Tracking: All memories now include a project field that captures the hostname and current working directory (e.g., "myserver:/home/user/project").

Environment Metadata: Set the MEMORY_METADATA environment variable to automatically include custom metadata in all memories:

export MEMORY_METADATA="server:production,team:engineering,region:us-west"

This metadata is automatically:

• Added to all new memories
• Included in memory embeddings for better search relevance
• Used in search queries to improve context matching

Memory Analytics Tool

A comprehensive CLI tool is included for analyzing memories:

# Quick start
./memory-analytics count    # Count memories by agent
./memory-analytics tags     # Analyze tag usage
./memory-analytics compare  # Compare agents
./memory-analytics all      # Run all analytics

See docs/MEMORY_ANALYTICS.md for detailed documentation.

Development

• npm run dev - Run in development mode
• npm run build - Build TypeScript
• npm run test - Run tests
• npm run lint - Run linter
• npm run typecheck - Type check