MemMachine

What is MemMachine?

MemMachine is an open-source long-term memory layer for AI agents and LLM-powered applications. It enables your AI to learn, store, and recall information from past sessions—transforming stateless chatbots into personalized, context-aware assistants.

Key Capabilities

• Episodic Memory: Graph-based conversational context that persists across sessions
• Profile Memory: Long-term user facts and preferences stored in SQL
• Working Memory: Short-term context for the current session
• Agent Memory Persistence: Memory that survives restarts, sessions, and even model changes

Quick Start

Get up and running in under 5 minutes:

Prerequisites: This code requires a running MemMachine Server. Start a server locally or create a free account on the MemMachine Platform.

pip install memmachine-client

from memmachine_client import import MemMachineClient

# Initialize the client
client = MemMachineClient(base_url="http://localhost:8080")

# Get or create a project
project = client.get_or_create_project(org_id="my_org", project_id="my_project")

# Create a memory instance for a user session
memory = project.memory(
    group_id="default",
    agent_id="travel_agent",
    user_id="alice",
    session_id="session_001"
)

# Add a memory
memory.add("I prefer aisle seats on flights", metadata={"category": "travel"})
# => [AddMemoryResult(uid='...')]

# Search memories
results = memory.search("What are my flight preferences?")
print(results.content.episodic_memory.long_term_memory.episodes[0].content)
# => "I prefer aisle seats on flights"

For full installation options (Docker, self-hosted, cloud), visit the Quick Start Guide.

Integrations

MemMachine works seamlessly with your favorite AI frameworks:

MCP Server Support

MemMachine includes a native Model Context Protocol (MCP) server for seamless integration with