MCP Hub
Back to servers

MemoVault

A personal memory system that provides AI assistants with long-term memory capabilities through semantic search and vector storage. It enables Claude Code to store, retrieve, and manage personal context and project preferences using flexible LLM backends.

Updated
Feb 4, 2026

MemoVault

A simplified personal memory system for AI assistants, designed for Claude Code integration via MCP.

Features

  • MCP Server: First-class integration with Claude Code
  • Flexible Backends: Support for OpenAI and Ollama (local) LLMs
  • Vector Search: Semantic memory retrieval using Qdrant
  • Simple JSON Storage: Lightweight option for basic use cases
  • Easy Configuration: Environment-based setup

Quick Start

Installation

pip install memovault

# For local embeddings (optional)
pip install memovault[local]

Basic Usage

from memovault import MemoVault

# Initialize with default settings (reads from .env)
mem = MemoVault()

# Add memories
mem.add("I prefer Python for backend development")
mem.add("My project deadline is March 15th")

# Search for relevant memories
results = mem.search("programming preferences")
for result in results:
    print(result.memory)

# Chat with memory context
response = mem.chat("What language should I use for my backend?")
print(response)

# Save memories to disk
mem.dump("./my_memories")

Claude Code Integration

  1. Configure MemoVault in your Claude Code settings:
{
  "mcpServers": {
    "memovault": {
      "command": "memovault-mcp",
      "env": {
        "MEMOVAULT_LLM_BACKEND": "openai",
        "MEMOVAULT_OPENAI_API_KEY": "sk-..."
      }
    }
  }
}
  1. Use memory commands in Claude Code:
    • "Remember that I prefer dark mode"
    • "What do you know about my preferences?"

Configuration

Copy .env.example to .env and customize:

# LLM Backend
MEMOVAULT_LLM_BACKEND=openai  # or "ollama"
MEMOVAULT_OPENAI_API_KEY=sk-...
MEMOVAULT_OPENAI_MODEL=gpt-4o-mini

# Embedder Backend
MEMOVAULT_EMBEDDER_BACKEND=openai  # or "ollama", "sentence_transformer"

# Memory Backend
MEMOVAULT_MEMORY_BACKEND=vector  # or "simple"

# Storage
MEMOVAULT_DATA_DIR=./memovault_data

MCP Tools

ToolDescription
add_memoryStore new information
search_memoriesFind relevant memories
chat_with_memoryMemory-enhanced chat
get_memoryRetrieve specific memory by ID
delete_memoryRemove a memory
list_memoriesShow recent memories
clear_memoriesClear all memories

Architecture

MemoVault/
├── src/memovault/
│   ├── core/           # Main MemoVault class
│   ├── memory/         # Memory backends (simple, vector)
│   ├── llm/            # LLM providers (OpenAI, Ollama)
│   ├── embedder/       # Embedding providers
│   ├── vecdb/          # Vector database (Qdrant)
│   ├── config/         # Configuration management
│   └── api/            # MCP server & REST API

License

MIT

Reviews

No reviews yet

Sign in to write a review