agent-magnet 0.1.3

Self-learning memory infrastructure for AI products

Agent Magnet

Self-learning memory infrastructure for AI products. It learns from what users do — not what they say.

Installation

pip install agent-magnet

Two Integration Modes

1. MCP Server (Free, Self-Hosted)

Run on your own infrastructure. You control your data.

Add to your MCP config (Claude Desktop / Cursor / any MCP client):

{
  "mcpServers": {
    "agent-magnet": {
      "command": "agent-magnet-mcp",
      "env": {
        "MAGNET_REDIS_URL": "your_redis_url",
        "MAGNET_OPENAI_KEY": "your_openai_key"
      }
    }
  }
}

Tools available:

• get_profile — get learned memory profile for a user
• inject_memory — get memory injection string for system prompt
• add_signal — record a behavioral signal
• get_cold_start — get onboarding profile for new users

2. Proxy (Hosted, Dashboard included)

Change one line. We handle the infrastructure.

from openai import OpenAI

client = OpenAI(
    api_key="mg_sk_...",
    base_url="https://magnet-gateway.onrender.com/v1",
    default_headers={"x-session-id": "user_123"}
)

Get your API key: agentmagnet.app

How It Learns

Magnet observes behavioral signals — corrections, rejections, implicit patterns — and builds a living profile per user. No configuration required.

Three memory layers:

• Behavioral (Redis) — real-time, every request
• Episodic (Qdrant) — semantic recall when relevant
• Knowledge (Neo4j) — long-term entity relationships

License

MIT