LibreAI / AI Agents / moltis
// agents · moltis-org/moltis

moltis

Secure persistent personal agent server in one Rust binary — sandboxed, multi-provider, on your hardware

★ 2.9k stars⑂ 356 forksMITupdated 2026-09
▦ visual — this project's README ships no embeddable screenshot,
so here's a placeholder. The guide below is complete regardless.
// project facts

Project facts

moltis is an open-source ai agents project by moltis-org (moltis-org/moltis on GitHub). It has 2,886 GitHub stars and 356 forks, is released under the MIT license, and was last updated on GitHub on 22 September 2026.

GitHub stars
2,886
Forks
356
License
MIT
Last updated on GitHub
22 September 2026
Category
AI Agents
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Clarify your goal

    Decide which channels (Telegram, WhatsApp, Discord, Teams, voice) and which LLM providers your personal agent should use.

  2. Get Moltis

    Install the single binary with the one-liner script, Homebrew, Docker, or cargo install from source.

  3. Install and configure

    Start the server, open its web UI, add your provider keys (they stay on your machine) and connect your channels.

  4. Run your first task

    Send your agent a message on a connected channel and watch it work in its sandboxed container.

// features

Why people love it

Single Rust binary

One binary with no Node.js, npm or other runtime — the workspace is about 59 modular crates you can audit independently.

Sandboxed execution

Every command runs in a sandboxed container, never on your host, and context files are scanned for threats.

Multi-provider LLMs

Works with multiple LLM providers using your own keys, which never leave your machine.

Many channels built in

Telegram, Signal, WhatsApp, Discord, Teams and voice are built in — no plugin marketplace to get supply-chain attacked through.

Memory and scheduling

Persistent memory, cross-session recall, automatic edit checkpoints and scheduling are built in.

MCP and remote exec

MCP servers, browser automation, and SSH or node-backed remote execution are supported.

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// run it

Run it yourself

  1. Clone the repo

    Clone Moltis if you want to build or inspect the source; most users install the binary in step 2.

    git clone https://github.com/moltis-org/moltis.git
    cd moltis
  2. Install the binary

    Use the official one-liner (macOS/Linux), Homebrew, or the Docker image as the README shows.

    curl -fsSL https://www.moltis.org/install.sh | sh
    # or: brew install moltis-org/tap/moltis
    # or: docker pull ghcr.io/moltis-org/moltis:latest
  3. Or build from source

    Install from the git source with Cargo (Rust 1.91+).

    cargo install moltis --git https://github.com/moltis-org/moltis
// use cases

What you can build

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// faq

Questions, answered

Who maintains Moltis?

It is maintained by the moltis-org team and contributors on GitHub.

Is Moltis free?

Yes, it is MIT-licensed and free to self-host. You pay only for any LLM provider usage with your own keys.

Does it need a paid API key?

It uses multi-provider LLMs with keys you supply, so model costs depend on your provider; the server software itself is free.

How does it compare to OpenClaw?

The README's comparison notes OpenClaw uses TypeScript with companion apps and a Node runtime, while Moltis is a single Rust binary with sandboxed execution built in.

How do I get started?

Run the one-liner install script (or brew/docker), start Moltis, add a provider key in the web UI and connect a channel like Telegram.

// 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 moltis is not the right fit.

Get moltis

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