Skip to main content

Universal memory module for LLMs with enhanced MCP integration

Project description

Greeum

PyPI version Python 3.10+ License: MIT

AI conversations that remember everything. No more repeating context every time.

⚡ Quick Start

# Install
pip install greeum

# Add your first memory
greeum memory add "Started working on the new dashboard project"

# Search later
greeum memory search "dashboard project"

That's it. Your AI now remembers.

✨ What It Does

🧠 Remembers context - AI recalls previous conversations and decisions ⚡ 280x faster search - Checkpoint-based memory retrieval 🔄 Works with any AI - GPT, Claude, or your custom model 🛡️ Your data stays yours - Local storage, no cloud required

🔧 Installation

Basic Setup

pip install greeum

With All Features

pip install greeum[all]  # includes vector search, embeddings

For Claude Code Users

# Install and start MCP server
pip install greeum
greeum mcp serve

📝 Usage

Adding Memories

# Add important context
greeum memory add "Client prefers minimal UI design"

# Add with expiration
greeum stm add "Working on login page today" --ttl 24h

Searching

# Find relevant memories
greeum memory search "UI design preferences" --count 5

# Search with options
greeum memory search "login" --count 10

Python API

from greeum import BlockManager, DatabaseManager

# Initialize
db_manager = DatabaseManager()
memory = BlockManager(db_manager)

# Add block to long-term memory
block = memory.add_block(
    context="User wants dark mode toggle",
    keywords=["dark", "mode", "toggle"],
    tags=["ui", "preference"],
    embedding=[],  # Auto-generated if empty
    importance=0.7
)

# Search memories
results = memory.search_memories("dark mode", limit=3)

🤖 Claude Integration

Setup MCP Server

Add to your Claude Desktop config:

{
  "mcpServers": {
    "greeum": {
      "command": "greeum",
      "args": ["mcp", "serve"],
      "env": {
        "GREEUM_DATA_DIR": "/path/to/your/data"
      }
    }
  }
}

Available Tools

  • add_memory - Store important context
  • search_memory - Find relevant memories
  • get_memory_stats - View memory statistics

📚 Documentation

🏗️ Architecture

Your Input → Working Memory → Cache → Checkpoints → Long-term Storage
             0.04ms          0.08ms   0.7ms        Permanent

Four-layer memory system optimized for speed and relevance.

📋 Version Updates

v2.1.1 (2025-08)

  • Enhanced search with temporal boost for recent information prioritization
  • Optimized codebase with 955 lines of code reduction and improved test architecture
  • Resolved import dependencies and improved memory management
  • Added intelligent date keyword detection for search result ranking
  • Improved test stability with BaseGreeumTestCase standardization
  • Performance optimizations with minimal overhead (+1.0%)

🤝 Contributing

  1. Fork the repository
  2. Create your feature branch
  3. Submit a pull request

See CONTRIBUTING.md for details.

📄 License

MIT License - see LICENSE file.


Greeum - Memory for AI that actually works. Made with ❤️ by the open source community.

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

greeum-2.2.5.tar.gz (227.7 kB view details)

Uploaded Source

Built Distribution

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

greeum-2.2.5-py3-none-any.whl (188.1 kB view details)

Uploaded Python 3

File details

Details for the file greeum-2.2.5.tar.gz.

File metadata

  • Download URL: greeum-2.2.5.tar.gz
  • Upload date:
  • Size: 227.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for greeum-2.2.5.tar.gz
Algorithm Hash digest
SHA256 04cc9164bc1f5245ad49bc9184a2f4fe0e1ae6286bdb3eef915324c08dd7eb53
MD5 ce2209272ab5f9110ba79dc82eaa1b76
BLAKE2b-256 2db398c1cc152ab2922c9ceadaed60c0f1625721a9fe3ae373e49d895d0f2df6

See more details on using hashes here.

File details

Details for the file greeum-2.2.5-py3-none-any.whl.

File metadata

  • Download URL: greeum-2.2.5-py3-none-any.whl
  • Upload date:
  • Size: 188.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for greeum-2.2.5-py3-none-any.whl
Algorithm Hash digest
SHA256 aa0b5fa8e5a5404b8ce61e5f828d9bfa12851481bbaee9c9a4fc7ff36cd3e62e
MD5 ee49309b4ee26764698ba755f1f7b7cc
BLAKE2b-256 52b7b80540b47c316479ab4f6070eb51b407eab74d9896311d78b7f2a6ff967c

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