Skip to main content

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 >= 3.13
  • 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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

super_memory_mcp-0.4.0.tar.gz (126.7 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

super_memory_mcp-0.4.0-py3-none-any.whl (13.5 kB view details)

Uploaded Python 3

File details

Details for the file super_memory_mcp-0.4.0.tar.gz.

File metadata

  • Download URL: super_memory_mcp-0.4.0.tar.gz
  • Upload date:
  • Size: 126.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.7 {"installer":{"name":"uv","version":"0.11.7","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for super_memory_mcp-0.4.0.tar.gz
Algorithm Hash digest
SHA256 4ef4650d6b5a8dee223b670f170839b8d0f135bb7fa5e6b1ea2345349f37c213
MD5 dccadfe85f6ab449ddd1052afe208470
BLAKE2b-256 4c1e5771decf1ee8435c550ecd0bcbf4cc33875c0aa8f1e8b92d49bdb42bb652

See more details on using hashes here.

File details

Details for the file super_memory_mcp-0.4.0-py3-none-any.whl.

File metadata

  • Download URL: super_memory_mcp-0.4.0-py3-none-any.whl
  • Upload date:
  • Size: 13.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.7 {"installer":{"name":"uv","version":"0.11.7","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for super_memory_mcp-0.4.0-py3-none-any.whl
Algorithm Hash digest
SHA256 1b9ade4d34b3e72234842115e7c021d8743e720f0df6dd131f2cf4064bfab733
MD5 b1eefee2f637936f866667dabd386176
BLAKE2b-256 090e9baff6dce6988405341b04c117209caec1f0320438d9ce60aa9904318c6e

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page