Metadata-Version: 2.4
Name: a-mem
Version: 0.2.5
Summary: Self-evolving memory system for AI agents with semantic search and knowledge graph capabilities. Includes MCP server for Claude and other AI assistants.
License: MIT License
        
        Copyright (c) 2025 AGI Research
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
Project-URL: Homepage, https://github.com/DiaaAj/a-mem-mcp
Project-URL: Bug Tracker, https://github.com/DiaaAj/a-mem-mcp/issues
Project-URL: Research Paper, https://arxiv.org/pdf/2502.12110
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Development Status :: 4 - Beta
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: sentence-transformers>=2.2.2
Requires-Dist: chromadb>=0.4.22
Requires-Dist: rank_bm25>=0.2.2
Requires-Dist: nltk>=3.8.1
Requires-Dist: litellm>=1.16.11
Requires-Dist: numpy>=1.24.3
Requires-Dist: scikit-learn>=1.3.2
Requires-Dist: openai>=1.3.7
Requires-Dist: requests>=2.31.0
Requires-Dist: mcp>=1.0.0
Requires-Dist: pydantic>=2.0.0
Requires-Dist: python-dotenv>=1.0.0
Dynamic: license-file

# A-MEM: Self-evolving memory for coding agents

<p align="center">
  <a href="https://pypi.org/project/a-mem/"><img src="https://img.shields.io/pypi/v/a-mem" alt="PyPI version"></a>
  <a href="https://pypi.org/project/a-mem/"><img src="https://img.shields.io/pypi/dm/a-mem" alt="PyPI downloads"></a>
  <a href="https://registry.modelcontextprotocol.io/?q=io.github.DiaaAj%2Fa-mem-mcp"><img src="https://img.shields.io/badge/MCP-Registry-blue" alt="MCP Registry"></a>
</p>

**mcp-name: io.github.DiaaAj/a-mem-mcp**

A-MEM is a self-evolving memory system for coding agents. Unlike simple vector stores, A-MEM automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships. Memories don't just get stored—they evolve and connect over time.

Currently tested with **Claude Code**. Support for other MCP-compatible agents is planned.

<img src="/Figure/cover.png">

## Quick Start

### Install

```bash
pip install a-mem
```

### Add to Claude Code

```bash
claude mcp add a-mem -s user -- a-mem-mcp \
  -e LLM_BACKEND=openai \
  -e LLM_MODEL=gpt-4o-mini \
  -e OPENAI_API_KEY=sk-...
```

That's it! A session-start hook installs automatically to remind Claude to use memory.

> **Note:** Memory is stored per-project in `./chroma_db`. For global memory across all projects, see [Memory Scope](#memory-scope).

### Uninstall

```bash
a-mem-uninstall-hook   # Remove hooks first
pip uninstall a-mem
```

## How It Works

```
t=0              t=1                t=2

                 ◉───◉             ◉───◉
 ◉               │                 ╱ │ ╲
                 ◉                ◉──┼──◉
                                     │
                                     ◉

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━▶
            self-evolving memory
```

1. **Add a memory** → A-MEM extracts keywords, context, and tags via LLM
2. **Find neighbors** → Searches for semantically similar existing memories
3. **Evolve** → Decides whether to link, strengthen connections, or update related memories
4. **Store** → Persists to ChromaDB with full metadata and relationships

The result: a knowledge graph that grows smarter over time, not just bigger.

## Features

**Self-Evolving Memory**
Memories aren't static. When you add new knowledge, A-MEM automatically finds related memories and strengthens connections, updates context, and evolves tags.

**Semantic + Structural Search**
Combines vector similarity with graph traversal. Find memories by meaning, then explore their connections.

## MCP Tools

A-MEM exposes 6 tools to your coding agent:

| Tool | Description |
|------|-------------|
| `add_memory_note` | Store new knowledge (async, returns immediately) |
| `search_memories` | Semantic search across all memories |
| `search_memories_agentic` | Search + follow graph connections |
| `read_memory_note` | Get full details of a specific memory |
| `update_memory_note` | Modify existing memory |
| `delete_memory_note` | Remove a memory |

### Example Usage

```python
# The agent calls these automatically, but here's what happens:

# Store a memory (returns task_id immediately)
add_memory_note(content="Auth uses JWT in httpOnly cookies, validated by AuthMiddleware")

# Search later
search_memories(query="authentication flow", k=5)

# Deep search with connections
search_memories_agentic(query="security", k=5)
```

## Advanced Configuration

### JSON Config

For more control, edit `~/.claude/settings.json` (global) or `.claude/settings.local.json` (project):

```json
{
  "mcpServers": {
    "a-mem": {
      "command": "a-mem-mcp",
      "env": {
        "LLM_BACKEND": "openai",
        "LLM_MODEL": "gpt-4o-mini",
        "OPENAI_API_KEY": "sk-..."
      }
    }
  }
}
```

### Environment Variables

| Variable | Description | Default |
|----------|-------------|---------|
| `LLM_BACKEND` | `openai`, `ollama`, `sglang`, `openrouter` | `openai` |
| `LLM_MODEL` | Model name | `gpt-4o-mini` |
| `OPENAI_API_KEY` | OpenAI API key | — |
| `EMBEDDING_MODEL` | Sentence transformer model | `all-MiniLM-L6-v2` |
| `CHROMA_DB_PATH` | Storage directory | `./chroma_db` |
| `EVO_THRESHOLD` | Evolution trigger threshold | `100` |

### Memory Scope

- **Project-specific** (default): Each project gets isolated memory in `./chroma_db`
- **Global**: Share across projects by setting `CHROMA_DB_PATH=~/.local/share/a-mem/chroma_db`

### Alternative Backends

**Ollama (local, free)**
```bash
claude mcp add a-mem -s user -- a-mem-mcp \
  -e LLM_BACKEND=ollama \
  -e LLM_MODEL=llama2
```

**OpenRouter (100+ models)**
```bash
claude mcp add a-mem -s user -- a-mem-mcp \
  -e LLM_BACKEND=openrouter \
  -e LLM_MODEL=anthropic/claude-3.5-sonnet \
  -e OPENROUTER_API_KEY=sk-or-...
```

### Hook Management (Claude Code)

The session-start hook reminds Claude to use memory tools. It installs automatically with Claude Code, but you can manage it manually:

```bash
a-mem-install-hook     # Install/reinstall hook
a-mem-uninstall-hook   # Remove hook completely
```

## Python API

Use A-MEM directly in Python (works with any agent or application):

```python
from agentic_memory.memory_system import AgenticMemorySystem

memory = AgenticMemorySystem(
    llm_backend="openai",
    llm_model="gpt-4o-mini"
)

# Add (auto-generates keywords, tags, context)
memory_id = memory.add_note("FastAPI app uses dependency injection for DB sessions")

# Search
results = memory.search("database patterns", k=5)

# Read full details
note = memory.read(memory_id)
print(note.keywords, note.tags, note.links)
```

## Research

A-MEM implements concepts from the paper:

> **A-MEM: Agentic Memory for LLM Agents**
> Xu et al., 2025
> [arXiv:2502.12110](https://arxiv.org/pdf/2502.12110)
