KI-Agenten
mem0
Drop-in persistent memory infrastructure for AI agents and apps.
★ 66,8 Tsd. SterneApache-2.0
Anleitung ansehen →Memori ist ein Open-Source-Projekt aus der Kategorie KI-Agenten von MemoriLabs (MemoriLabs/Memori auf GitHub). Es hat 17.143 Sterne auf GitHub und 3.712 Forks, wird unter der Lizenz NOASSERTION veröffentlicht und wurde zuletzt am 3. Oktober 2026 auf GitHub aktualisiert.
Agent-native memory infrastructure - structured, persistent memory for production agents
Decide which entities (users, agents, places) and processes memories should be attributed to.
Install the Python or TypeScript SDK, or connect an agent through the one-command MCP setup.
Set your Memori and LLM provider keys and attribute conversations to entities and processes.
Hold a short conversation, start a new session, and check that Memori recalls the facts.
Turns conversations and agent execution into structured state that persists across sessions.
Works across model providers rather than tying memory to one vendor.
BYODB support lets memory live in the data infrastructure you already operate.
Ships as a persistent memory provider for Hermes Agent and OpenClaw, plus an MCP server for clients like Claude Code and Cursor.
A hosted dashboard offers Memories, Analytics, a Playground and API key management.
Managed cloud, single-tenant cloud, VPC and on-premises deployment models.
Get the source code from GitHub and enter the project directory.
git clone https://github.com/MemoriLabs/Memori.git
cd MemoriChoose the Python or TypeScript package.
pip install memori
# TypeScript: npm install @memorilabs/memoriThe README quickstart persists a conversation and shows automatic recall in a later session; it needs MEMORI_API_KEY and OPENAI_API_KEY in the environment.
# Set MEMORI_API_KEY and OPENAI_API_KEY, then run the README quickstart exampleIt is maintained by MemoriLabs on GitHub.
The SDKs are Apache-2.0 licensed open source per the README. Memori Cloud is a managed service with quota management via its dashboard/CLI.
The quickstart uses a Memori API key plus your LLM provider key (the example uses OpenAI); BYODB and self-managed setups change what you need - see the docs.
Compared with rolling your own vector-store memory, Memori adds structured attribution, entity/process scoping and enterprise deployment options as a managed layer.
Run pip install memori, set the API keys from the README quickstart, and run the two-session recall example.
Drop-in persistent memory infrastructure for AI agents and apps.
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