LibreAI / AI Agents / atmosphere
// agents · Atmosphere/atmosphere

atmosphere

A portable AI agent runtime for the JVM — write one @Agent, run it on any Java AI stack.

★ 3.8k stars⑂ 764 forksApache-2.0updated 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

atmosphere is an open-source ai agents project by Atmosphere (Atmosphere/atmosphere on GitHub). It has 3,818 GitHub stars and 764 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 6 October 2026.

GitHub stars
3,818
Forks
764
License
Apache-2.0
Last updated on GitHub
6 October 2026
Category
AI Agents
Listing
Full install guide
Official site
Official site
// how it works

How it works

  1. Clarify your goal

    Decide the first concrete outcome you want from it, so you can pick the right example, template or mode instead of exploring everything at once.

  2. Get the project

    Clone the repository (or install the published package) and skim its README quick start for the requirements for your platform.

  3. Install and configure

    Run the documented install step and set any required configuration — such as provider keys, data sources or local services — before the first run.

  4. Run your first task

    Execute the smallest documented example end to end, confirm the output is what you expected, then adapt it to your real data or workflow.

// features

Why people love it

One agent, many runtimes

Write an @Agent once and swap the runtime adapter — built-in, Spring AI, LangChain4j and more — without rewriting the agent.

Deep agents, batteries included

Long-term memory, a maintained plan (write_todos), a bounded virtual filesystem and sub-agent delegation on @Coordinator.

Every modern protocol

MCP, A2A and AG-UI support, streamed over WebSocket, SSE, gRPC or WebTransport/HTTP3.

Enterprise controls

Human approvals, policy engines (OPA Rego, AWS Cedar), audit sinks to Kafka/Postgres and an admin control plane.

Durable by design

Durable sessions (SQLite/Redis), checkpoints and a sandbox module for long-running agents.

CLI scaffolding

atmosphere new creates apps from templates, atmosphere run launches samples, and atmosphere import turns a SKILL.md into a project.

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// run it

Run it yourself

  1. Clone the repository

    Get the source so you can inspect, configure and run it locally.

    git clone https://github.com/Atmosphere/atmosphere.git
    cd atmosphere
  2. Install the CLI

    Install Atmosphere via Homebrew or the install script.

    brew install Atmosphere/tap/atmosphere
    # Or: curl -fsSL https://raw.githubusercontent.com/Atmosphere/atmosphere/main/cli/install.sh | sh
  3. Create and run an agent

    Scaffold a chat agent, set your model key, and run it — swap --runtime to target Spring AI or LangChain4j.

    atmosphere new my-agent --template ai-chat
    cd my-agent
    LLM_API_KEY=your-key ./mvnw spring-boot:run
// use cases

What you can build

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// faq

Questions, answered

Who maintains atmosphere?

It is maintained by Atmosphere on GitHub (Atmosphere/atmosphere), where the source, issues and releases live.

Is it free to use?

Yes — it is free and open source under Apache-2.0, which permits use, modification and commercial redistribution, with licence/notice retention.

Does it need a paid API key?

Yes — agents call an LLM through the runtime you choose, so you supply that provider's API key (the samples read LLM_API_KEY).

How does it compare to building directly on Spring AI or LangChain4j alone?

Compared with building directly on Spring AI or LangChain4j alone, atmosphere's distinguishing focus is: a portable AI agent runtime for the JVM — write one @Agent, run it on any Java AI stack. Pick it when that focus matches your need; the alternative may suit you better if its broader or different scope is the priority.

How do I get started?

Clone https://github.com/Atmosphere/atmosphere (or install its published package), follow the README quick start to install and configure it, then run the smallest documented example — the Run section on this page mirrors those steps.

// 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 atmosphere is not the right fit.

Get atmosphere

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