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A semantic memory storage and retrieval system using LanceDB and sentence transformers

Project description

Super-Memory

A semantic memory storage and retrieval MCP (Model Context Protocol) server using LanceDB and sentence transformers.

What is Super-Memory?

Super-Memory gives your AI agents long-term memory across sessions. It stores and retrieves information using semantic embeddings, so agents can recall relevant context from previous conversations, files, and web pages.

Features

  • Semantic search - Query memories by meaning, not just keywords
  • File memory - Read and store local file contents
  • Web memory - Fetch and store web page contents
  • Boomerang context - Special support for Boomerang Protocol session state
  • Local storage - All data stays on your machine in ./memory_data

Tools

Tool Description
save_to_memory Store text with optional metadata
save_file_memory Read a file and store its content
save_web_memory Fetch a URL and store its content
query_memory Semantic search across all memories
list_sources List all stored sources
recall_source Retrieve exact source by path
save_boomerang_context Save Boomerang session context
get_boomerang_context Retrieve Boomerang session context

Installation

Using uv (recommended)

uv tool install super-memory-mcp

Using pip

pip install super-memory-mcp

Manual / Development

git clone https://github.com/Veedubin/Super-Memory.git
cd Super-Memory
uv sync
uv run super-memory-mcp

OpenCode Configuration

Add to your .opencode/opencode.json:

{
  "mcp": {
    "super-memory-mcp": {
      "type": "local",
      "command": ["uv", "run", "super-memory-mcp"],
      "enabled": true
    }
  }
}

Or if installed with uv tool:

{
  "mcp": {
    "super-memory-mcp": {
      "type": "local",
      "command": ["super-memory-mcp"],
      "enabled": true
    }
  }
}

Requirements

  • Python >= 3.12
  • CUDA (optional but recommended) - falls back to CPU automatically
  • ~500MB disk space for the embedding model (downloaded on first run)

First Run

On first startup, Super-Memory will download the BAAI/bge-large-en-v1.5 sentence transformer model. This may take a few minutes depending on your internet connection.

Data Storage

Memories are stored locally in a ./memory_data directory relative to where you run the command. Each project should ideally run Super-Memory from its own directory to keep project-specific memories separate.

License

MIT License - see LICENSE

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