memorious-mcp

A local and persistent semantic memory server for AI assistants using the Model Context Protocol (MCP). Built with ChromaDB for vector similarity search and FastMCP for efficient tool implementation.

Runs entirely locally - no data ever leaves your machine.

Overview

memorious-mcp provides AI assistants with long-term memory capabilities through three core operations: store, recall, and forget. It uses ChromaDB's vector database to enable semantic similarity search, allowing assistants to retrieve relevant memories even when the exact wording differs from the original storage. All processing and storage happens locally on your machine, ensuring complete privacy and security.

Key Features

• 100% Local & Private: All data processing and storage happens on your machine - nothing goes to the cloud
• Persistent Memory: Data persists across sessions using ChromaDB's disk-based storage
• Semantic Search: Vector embeddings enable similarity-based memory retrieval
• Simple API: Three intuitive tools for memory management
• FastMCP Integration: Built on FastMCP for efficient MCP server implementation
• Canonical Key Design: Optimized for short, embedding-friendly keys (1-5 words)
• Secure by Design: No external API calls or cloud dependencies required

Tools

store

Store facts, preferences, or information with short canonical keys optimized for vector similarity.

Parameters:

• key (string): Short, canonical key (1-5 words, space-separated)
• value (string): The actual information to store

recall

Retrieve stored memories using semantic similarity search.

Parameters:

• key (string): Query key for similarity search
• top_k (int, default: 3): Maximum number of results to return

forget

Delete memories matching a query key.

Parameters:

• key (string): Query key to find memories to delete
• top_k (int, default: 3): Number of nearest matches to consider

Installation

# Install via uvx (recommended)
uvx memorious-mcp

# Or install in virtual environment
uv sync
uv run memorious-mcp

Configuration

Add to your MCP client configuration:

{
  "mcpServers": {
    "memorious": {
      "command": "uvx",
      "args": ["memorious-mcp"]
    }
  }
}

Use Cases

• Personal Assistant Memory: Remember user preferences, habits, and personal information
• Context Preservation: Maintain conversation context across sessions
• Knowledge Management: Store and retrieve project-specific information
• Personalization: Enable AI assistants to provide personalized responses based on stored preferences
• Privacy-First AI: Keep sensitive personal data local while still having persistent memory

Technical Details

• Backend: ChromaDB with persistent disk storage
• Embeddings: Uses ChromaDB's default embedding function (local processing)
• Storage Location: ./.memorious directory (configurable)
• Python Version: Requires Python ≥3.12
• License: MIT
• Privacy: No network requests, no cloud dependencies, all data stays local

The server is designed for local/CLI integrations using stdio transport, making it suitable for personal AI assistants and development workflows where privacy and data security are paramount.