LibreAI / AI Agents / forkd
// agents · deeplethe/forkd

forkd

Fork() for AI agent microVMs — spawn 100 KVM-isolated children in ~100ms from a warm parent

★ 2.9k stars⑂ 227 forksApache-2.0updated 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

forkd is an open-source ai agents project by deeplethe (deeplethe/forkd on GitHub). It has 2,923 GitHub stars and 227 forks, is released under the Apache-2.0 license, and was last updated on GitHub on 14 September 2026.

Repository
deeplethe/forkd
GitHub stars
2,923
Forks
227
License
Apache-2.0
Last updated on GitHub
14 September 2026
Category
AI Agents
Listing
Full install guide
// how it works

How it works

  1. Clarify your goal

    Decide your fan-out shape: parallel agent evals, per-user code execution, untrusted CI, or fork-per-turn code interpretation.

  2. Get forkd

    Install the daemon (or build from source with Cargo) on a Linux host with KVM and Firecracker.

  3. Install and configure

    Run forkd doctor / quickstart to preflight KVM, Firecracker and networking, then pull or bake a warm parent snapshot.

  4. Run your first fork

    Fork a few children from the snapshot tag, run a task in one, and check its timing and isolation.

// features

Why people love it

Fast microVM forks

The README reports spawning 100 children in about 100 ms from a warm parent snapshot, sharing memory copy-on-write until they diverge.

Live BRANCH

Pause a running sandbox, snapshot its in-flight state and resume — about 150 ms, with v0.4 live mode cutting the pause window further.

KVM isolation

Each child is a separate Firecracker microVM with real KVM isolation, not just a container namespace.

Diff-snapshot chains

Stack snapshot layers (e.g. Python base, then numpy, then pandas) that the daemon assembles in one pass at spawn time.

Snapshot hub

Pull portable prebaked snapshots such as a LangGraph parent image, or publish your own.

SDKs and MCP

Python SDK (pip install forkd), TypeScript SDK (@deeplethe/forkd) and an MCP server (pip install forkd-mcp) for Claude and Cursor.

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// run it

Run it yourself

  1. Clone the repo

    Clone forkd and enter the directory.

    git clone https://github.com/deeplethe/forkd.git
    cd forkd
  2. Quickstart preflight

    quickstart preflights the host (KVM, Firecracker, kernel image), bakes or pulls a Python snapshot, then forks 10 children with per-child timings.

    sudo -E forkd quickstart
  3. Pull and fork a snapshot

    Pull a portable snapshot from the hub and fork children from it.

    forkd pull deeplethe/langgraph-react
    sudo -E forkd fork --tag langgraph -n 3 --per-child-netns
// use cases

What you can build

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// faq

Questions, answered

Who maintains forkd?

It is maintained by deeplethe and contributors on GitHub.

Is forkd free?

Yes, it is Apache-2.0 licensed and self-hosted on your own Linux/KVM host, with no per-second cloud sandbox fees.

Does it need a paid API key?

No — forkd is sandbox infrastructure, not an LLM service. Your agents inside the VMs use whatever model keys you give them.

How does it compare to containers or managed sandbox SaaS?

Containers share a kernel; forkd gives each child its own microVM with KVM isolation, and unlike managed SaaS it runs on your own hardware.

How do I get started?

On a KVM-capable Linux host, install forkd, run sudo -E forkd quickstart, then forkd pull a snapshot and fork your first children.

// 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 forkd is not the right fit.

Get forkd

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