Quick Start

Installation

From source

cargo install --path crates/mnemo-cli

With Docker

docker pull ghcr.io/mnemo-ai/mnemo:latest
docker run -v mnemo-data:/data ghcr.io/mnemo-ai/mnemo:latest

Running

Basic (embedded DuckDB, noop embeddings)

mnemo --db-path my-agent.db

With OpenAI embeddings

export OPENAI_API_KEY=sk-...
mnemo --db-path my-agent.db

With PostgreSQL backend

mnemo --postgres-url "postgres://$POSTGRES_USER:$POSTGRES_PASSWORD@localhost/mnemo"

With REST API

mnemo --db-path my-agent.db --rest-port 8080

Claude Desktop Integration

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "mnemo": {
      "command": "mnemo",
      "args": ["--db-path", "/path/to/memory.db"],
      "env": {
        "OPENAI_API_KEY": "sk-..."
      }
    }
  }
}

Python SDK

pip install mnemo-db   # `mnemo` itself is held by a 2021 notebook project

from mnemo import MnemoClient

client = MnemoClient(db_path="agent.db")
result = client.remember("The user prefers dark mode")
memories = client.recall("user preferences")

First Operations

Once running, the agent (or you via MCP client) can:

1. Store a memory: mnemo.remember with content and optional metadata
2. Retrieve memories: mnemo.recall with a natural language query
3. Share with other agents: mnemo.share to grant access
4. Verify integrity: mnemo.verify to check hash chain consistency