LibreAI / AI Agents / Memori
// agents · MemoriLabs/Memori

Memori

Agent-native memory infrastructure - structured, persistent memory for production agents

★ 17.1k stars⑂ 3.7k forksNOASSERTIONupdated 2026-10
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

Memori is an open-source ai agents project by MemoriLabs (MemoriLabs/Memori on GitHub). It has 17,143 GitHub stars and 3,712 forks, is released under the NOASSERTION license, and was last updated on GitHub on 3 October 2026.

GitHub stars
17,143
Forks
3,712
License
NOASSERTION
Last updated on GitHub
3 October 2026
Category
AI Agents
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Plan your memory model

    Decide which entities (users, agents, places) and processes memories should be attributed to.

  2. Get Memori

    Install the Python or TypeScript SDK, or connect an agent through the one-command MCP setup.

  3. Configure attribution and keys

    Set your Memori and LLM provider keys and attribute conversations to entities and processes.

  4. Run your first remembered conversation

    Hold a short conversation, start a new session, and check that Memori recalls the facts.

// features

Why people love it

Structured persistent memory

Turns conversations and agent execution into structured state that persists across sessions.

LLM-agnostic

Works across model providers rather than tying memory to one vendor.

Bring your own database

BYODB support lets memory live in the data infrastructure you already operate.

Agent integrations

Ships as a persistent memory provider for Hermes Agent and OpenClaw, plus an MCP server for clients like Claude Code and Cursor.

Dashboard and analytics

A hosted dashboard offers Memories, Analytics, a Playground and API key management.

Enterprise deployment options

Managed cloud, single-tenant cloud, VPC and on-premises deployment models.

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// run it

Run it yourself

  1. Clone the repository

    Get the source code from GitHub and enter the project directory.

    git clone https://github.com/MemoriLabs/Memori.git
    cd Memori
  2. Install the SDK

    Choose the Python or TypeScript package.

    pip install memori
    # TypeScript: npm install @memorilabs/memori
  3. Run the quickstart

    The 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 example
// use cases

What you can build

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// faq

Questions, answered

Who maintains this project?

It is maintained by MemoriLabs on GitHub.

Is it free to use?

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.

Does it need a paid API key?

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.

How does it compare to alternatives?

Compared with rolling your own vector-store memory, Memori adds structured attribution, entity/process scoping and enterprise deployment options as a managed layer.

How do I get started?

Run pip install memori, set the API keys from the README quickstart, and run the two-session recall example.

// keep exploring

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// alternatives

Alternatives in AI Agents

The most-starred other AI Agents projects in the LibreAI catalogue — the realistic shortlist if Memori is not the right fit.

Get Memori

Free and open — grab the source, star the repo, and start creating.