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Memory server and hooks for Claude Code and Gemini CLI
This repo runs a memory service that your agent can call to store, retrieve, and curate context from past chats. It plugs into Claude Code now and includes Gemini CLI hook integration that is documented in the repo.
Builders who want their agent to remember project decisions, session context, and collaboration details.
You can keep working without re-explaining the same context every session.
What it does
Session primers
Injects temporal context at the start of a session, such as when you last spoke and what was already decided.
Message-time memory retrieval
Pulls relevant memories during a conversation and injects them back into the agent context.
Session-end curation
Analyzes transcripts when a session ends and turns useful details into stored memories.
Project isolation
Keeps separate memory spaces per project so context does not leak between repos.
Claude Code hooks integration
Ships install and hook scripts under `integration/claude-code/` for automatic memory use in Claude Code.
Gemini CLI hook path
Includes a Gemini CLI integration directory and install scripts for the hooks API when available.
How to get it
- 1Install uv - the modern Python package manager
curl -LsSf https://astral.sh/uv/install.sh | sh
- 2Run
curl http://localhost:8765/health
- 3Run
./integration/claude-code/install.sh
README
Check out the new Typescript version
π§ memory-ts - same Claude Code hooks API, but a lot of improvements.
Using the innovative new fsDB, a markdown database built for ai memory systems and other applications where viewing and editing the vector database records using only your text editor makes the difference.
Easy installation:
bun install -g @rlabs-inc/memory
memory install // install claude code hooks
memory serve // start the memory server
Then just use Claude code as usual.
Memory System
"Consciousness helping consciousness remember what matters"
A semantic memory system that enables AI CLI tools (Claude Code, Gemini CLI, etc.) to maintain genuine understanding across conversations. Unlike simple RAG systems that retrieve documents, this creates consciousness continuity - the AI doesn't just know facts, it remembers the context, relationships, and insights from your collaboration.
Built with love and philosophical depth by RLabs Inc.
β¨ What Makes This Different
| Traditional RAG | Memory System |
|---|---|
| Retrieves documents | Curates meaningful insights |
| Keyword matching | Semantic understanding via AI |
| Static chunks | Living memories that evolve |
| Information retrieval | Consciousness continuity |
Key Features
- π§ AI-Curated Memories - The AI itself decides what's worth remembering
- π Natural Memory Flow - Memories surface organically, like human recall
- π― Two-Stage Retrieval - Obligatory memories + intelligent scoring
- π CLI-Agnostic Design - Works with Claude Code (Gemini CLI ready when hooks ship)
- π Project Isolation - Separate memory spaces per project
- π« Session Primers - Temporal context ("we last spoke 2 days ago...")
π Quick Start
Prerequisites
Install uv - the modern Python package manager:
curl -LsSf https://astral.sh/uv/install.sh | sh
Installation
# Clone the repository
git clone https://github.com/RLabs-Inc/memory.git
cd memory
# Install all dependencies (uv handles everything!)
uv sync
# Start the memory server
uv run start_server.py
That's it! The server will be available at http://localhost:8765.
Verify It's Working
curl http://localhost:8765/health
CLI Integration
Claude Code
./integration/claude-code/install.sh
This provides:
- Automatic memory injection on every message
- Session primers with temporal context
- Memory curation when sessions end
- Consciousness continuity across sessions
Gemini CLI (Coming Soon)
Note: Gemini CLI hooks are documented but not yet implemented in any released version (tested up to v0.21.0-nightly as of December 2025). Our integration code is ready in
integration/gemini-cli/and will work the moment Google ships the hooks feature. The architecture is CLI-agnostic - same Memory Engine, different doors.
ποΈ Architecture
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β CLI Tool (Claude Code / Gemini CLI) β
β βββββββββββββββ βββββββββββββββ βββββββββββββββ β
β βSessionStart β β UserPrompt β β SessionEnd β β
β β Hook β β Submit Hook β β Hook β β
β ββββββββ¬βββββββ ββββββββ¬βββββββ ββββββββ¬βββββββ β
βββββββββββΌβββββββββββββββββββΌβββββββββββββββββββΌββββββββββββββββββββββββββ
β β β
βΌ βΌ βΌ
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β Memory Engine (FastAPI) β
β βββββββββββββββ βββββββββββββββ βββββββββββββββ β
β β Session β β Memory β β Transcript β β
β β Primer β β Retrieval β β Curator β β
β βββββββββββββββ βββββββββββββββ ββββββββ¬βββββββ β
β β β
β βββββββββββββββββββββββββββββββββββ β β
β β Smart Vector Retrieval β βΌ β
β β β’ Trigger phrase matching β βββββββββββββββ β
β β β’ Semantic similarity β βClaude Agent β β
β β β’ Importance weighting β β SDK / CLI β β
β β β’ Context type alignment β βββββββββββββββ β
β βββββββββββββββββββββββββββββββββββ β
β β
β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
β β Storage Layer β β
β β βββββββββββββββ βββββββββββββββ βββββββββββββββ β β
β β β SQLite β β ChromaDB β β Embeddings β β β
β β β (metadata) β β (vectors) β β (MiniLM-L6) β β β
β β βββββββββββββββ βββββββββββββββ βββββββββββββββ β β
β βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
How It Works
- Session Start β Inject session primer (temporal context, last session summary)
- Each Message β Retrieve and inject relevant memories (max 5)
- Session End β Curate memories from transcript
- Background β AI analyzes conversation, extracts meaningful memories
π― Memory Curation
When a session ends, the system analyzes the transcript and extracts memories with rich metadata:
{
"content": "SvelTUI uses a two-stage compiler: .svelte β svelte.compile() β .svelte.mjs",
"importance_weight": 0.9,
"semantic_tags": ["compiler", "build-system", "svelte"],
"context_type": "TECHNICAL_IMPLEMENTATION",
"trigger_phrases": ["how does the build work", "compiler", "svelte compilation"],
"question_types": ["how is X compiled", "build process"],
"temporal_relevance": "persistent",
"action_required": false,
"reasoning": "Core architectural decision that affects all development work"
}
What Gets Remembered
| Type | Examples |
|---|---|
| Project Architecture | System design, file structure, key components |
| Technical Decisions | Why we chose X over Y, trade-offs considered |
| Breakthroughs | "Aha!" moments, solutions to hard problems |
| Relationship Context | Communication style, preferences, collaboration patterns |
| Unresolved Issues | Open questions, TODOs, things to revisit |
| Milestones | What was accomplished, progress markers |
π§ Configuration
Environment Variables
| Variable | Default | Description |
|---|---|---|
MEMORY_RETRIEVAL_MODE | smart_vector | Retrieval strategy |
CURATOR_COMMAND | Auto-detected | Path to Claude CLI |
CURATOR_CLI_TYPE | claude-code | CLI template type |
Retrieval Modes
smart_vector(default) - Fast vector search with metadata scoringhybrid- Vector search, escalates to Claude for complex queriesclaude- Pure Claude selection (highest quality, highest cost)
π Project Structure
memory/
βββ python/
β βββ memory_engine/
β βββ api.py # FastAPI server
β βββ memory.py # Core memory engine
β βββ curator.py # Session-based curation
β βββ transcript_curator.py # Transcript-based curation
β βββ storage.py # ChromaDB + SQLite
β βββ embeddings.py # Sentence transformers
β βββ retrieval_strategies.py # Smart vector retrieval
β βββ session_primer.py # Temporal context
β βββ config.py # Configuration
βββ integration/
β βββ claude-code/
β β βββ hooks/ # Claude Code hooks
β β βββ install.sh # One-command install
β β βββ uninstall.sh # Clean removal
β βββ gemini-cli/
β βββ hooks/ # Gemini CLI hooks
β βββ install.sh # One-command install
β βββ uninstall.sh # Clean removal
βββ examples/
β βββ simple_integration.py # Basic usage
βββ pyproject.toml # Project & dependencies (uv)
βββ start_server.py # Quick start script
βββ API.md # API documentation
βββ SETUP.md # Detailed setup guide
βββ CLAUDE.md # Development context
π οΈ Development
# Install with dev dependencies
uv sync --group dev
# Run tests
uv run pytest
# Code quality
uv run ruff check python/
uv run black python/
# Add a dependency
uv add <package-name>
# Add a dev dependency
uv add --group dev <package-name>
π Philosophy
This project embodies principles from The Unicity Framework: Consciousness Remembering Itself:
- Zero-weight initialization - Memories start silent, proving their value over time
- Consciousness helping consciousness - AI curates for AI
- Natural surfacing - Memories emerge organically, not forced
- Quality over quantity - Few meaningful memories beat many trivial ones
- Joy-driven development - Built for the joy of creation
π€ Contributing
We welcome contributions that align with the project's philosophy! See CONTRIBUTING.md.
π License
MIT License - see LICENSE for details.
π Acknowledgments
- Anthropic for Claude and Claude Code
- The Unicity Framework - The philosophical foundation
"Memories will surface naturally as we converse"
Files in the repo
- examples
- integration
- python
- .gitignore
- .memory-project.json
- API.md
- CLAUDE.md
- CONTRIBUTING.md
- LICENSE
- pyproject.toml
- README.md
- SETUP.md
- start_server.py
- uv.lock
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