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Data & context

MemMachine

Distinct episodic, profile, and working-memory layers behind a shared agent memory service.

Overview

Research summary

MemMachine is a memory layer for agents and language-model applications that need context across sessions or restarts. It separates episodic conversational information, longer-lived user profile facts, and working context, using graph and SQL storage for different memory functions. Applications connect through client libraries to a running server and can store or retrieve information independently of a particular model. The open-source server can be self-hosted, while the project's managed platform is a separate deployment option. It is memory infrastructure rather than an agent orchestration framework.

Repository summary

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Open issues
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Last push
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Commits, 90 days
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Repository activity
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Version
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Recorded catalogue figures. View repository data and provenance →

Classification

Pricing & services

Paid services unknown

Whether the provider offers paid products or services has not been established.

Licence scope

Implementation

Recorded implementation details and interfaces for MemMachine.

Implementation details

Python memory server and client libraries

Languages
Python
Repository type
source

Recorded interfaces and capabilities

Licence scope

Repository

Repository snapshots, release information and recorded maintenance signals.

Repository snapshot

MemMachine/MemMachine ↗

Stars
Unavailable
Open issues
Unavailable
Last push
Unavailable
Commits, 90 days
Unavailable
Repository activity
Not scored
Archived
Not recorded

Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).

Maintenance and provenance

Catalogue snapshot
2026-10-06

Documentation

Recorded references and research provenance for this entry.

Recorded sources 4

Research metadata

Research date
2026-10-02
Catalogue snapshot
2026-10-06

Community & social 2 channels

Communities