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Alternatives

Products that do what Keystone – building self-configuring agents does

When cloning a repo, we kept hitting the same wall: no Dockerfile, no dev container, no clear path to running it. Asking an agent to fix it directly on your system is risky, as it can clear Docker config, change kernel settings, downgrade packages without warning. Keystone runs the agent inside a Modal sandbox with its own Docker daemon. It iterates until tests pass, then hands you a .devcontainer/ you can just check in. Now your repo knows how to run itself!

  1. 1
    Keystone125

    Teach your repo how to run itself

    Mar 2026

  2. 2

    Open source DevOps agent for devs who just want to ship

    Dec 2025

  3. 3

    Open-source DevOps agent to secure & manage production infra

    2025

  4. 4
    zero94

    One command to deploy Docker containers to your own server

    Apr 2026

  5. 5

    AI-native Business Intelligence on your own infrastructure

    2025

  6. 6BY
  7. 7

    Global CDN, zero config TLS, free custom domains

    2023

  8. 8

    Open-source homeserver OS with a built-in AI agent

    Jul 2026 · livinity.io

  9. 9
    Refuse84

    Block vulnerable package installs for you and your AI

    Jun 2026 · refuse.dev

  10. 10
    fline9

    Your agent ships the repo. We build it and run it.

    24d ago · dev.fline.sh

  11. 11DR
  12. 12

    lambdock - Modern, hyper-hackable, Wayland-native desktop dock application (C and Guile Scheme + GTK4) w/ REPL

    26d ago · codeberg.org

  13. 13RA

    Hi HN folks, I have been building AI agents for quite some time now. The shift has gone from LLM + Tools → LLM Workflows → Agent + Tools + Memory, and now we are finally seeing true agency emerge: agents as systems composed of tools, command-line access, fine-grained system capabilities, and memory. This way of building agents is powerful, and I believe it is here to stay. But the real question is: are the systems powering these agents ready for that future? I do not think so. Using Docker for a single agent is not going to scale well, because agents need to be lightweight and fast. LLMs…

    Mar 2026 · github.com

  14. 14RY
  15. 15

    Run every docker-compose project at once, no port wars

    19d ago · mdocker.coding9.de

  16. 16GA
  17. 17IB

    Link: https://docs.trysoma.ai/ For the past ~9 months I’ve been building Soma, an open-source AI agent & workflow runtime written in Rust, with a TypeScript SDK (Python coming soon). It’s not a framework; it’s meant to sit underneath whatever agent/tooling code you already write (Vercel AI SDK, LangChain, custom code, etc.). It provides features around your framework + a better DX for building agents. I’ve tried to take a Next.JS model: open-source, good DX, self-deployable. I originally set out to build a vertical back-office/operations product for SMEs. I needed a…

    Dec 2025 · docs.trysoma.ai

  18. 18RC

    Hi HN, this is Cesar and Rodny, developers of an open-source container runtime called Sysbox, and co-founders of a startup called Nestybox (YC S20). We launched on HN almost a year ago and got excellent feedback then (https://news.ycombinator.com/item?id=24084758). Happy to say that over the past year, Sysbox has continued to gain traction, particularly for securing containers in production, CI/CD, and containerized dev environments. We wanted to announce an important new feature: integration between Sysbox and Kubernetes. As a quick refresher, Sysbox is a "runc" that…

    2021

  19. 19AL

    Hi HN, I built agentspace because I kept seeing tmux recommended for keeping Claude Code sessions alive over SSH. I find multiplexers painful because they subtly change shell behavior in ways I always forget. They also do not offer a standardized way to run highly permissive agents in a safe way. I also tried worktrees, but it just feels awkward to manage work in that way. Docker can help with all of this, so I thought up a workflow and used some shell aliases to automate spawning Claude/Codex agents into docker containers. I ended up creating a cli to wrap all these methods and would…

    Jun 2026 · github.com

  20. 20RM

    RunAgent eliminates the complexity of AI agent deployment across different frameworks and languages. Today's developers face deployment nightmares with fragmented frameworks (LlamaIndex, LangChain, LangGraph, CrewAI, Letta, Agno, etc.) each requiring different deployment processes, creating unnecessary friction. The Solution: Like MCP (Model Context Protocol), RunAgent provides a standardized approach to agent deployment. Developers simply provide a config file and their agent code - RunAgent handles the rest with REST API and WebSocket (Streaming and non streaming). Our open-source platform…

    2025 · github.com

  21. 21IB

    I got sick of: - Re-writing the same Terraform for the same common AWS infrastructure - Re-writing the same Rails code to build the same webapp - Re-configuring the same monitoring systems & CI/CD pipelines - Spending a week in dependency & configuration hell wiring it all together When I was launching my first two startups, I wished I had a strong starting point with all of the best practices & technology configured out-of-the-box. Every tool I found wanted to lock me in to some PaaS provider (that might not even exist in a year) who wanted to take a premium on my infrastructure spend…

    2024

  22. 22SA

    Hi HN, This is a project I've been working on since the beginning of 2025 full time, without funding. Coding agents have fundamentally changed the way we write software. When you let an agent write code, pull dependencies, and run scripts, you are delegating trust while still keeping the responsibility. You shouldn't have to choose between moving fast with agents and maintaining basic control over your host machine. Normally, we just inspect the final result, treating the app like a black box. Most security tools only sandbox the app runtime and ignore the build phase. CapaKit is my attempt…

    Jun 2026 · capakit.com

  23. 23LY

    We spoke to dozens of devs trying to deploy agents in prod. We found that most of them have the following dilemma (and end up not deploying because of this): giving the agents freedom to choose from a list of tools while guaranteeing that every call stays secure, fast, and actually works. That’s why we built MCPglue. It gives you the reliability you’re looking for when deploying in prod, and agents the custom tools they need to do their job well. Here’s a walkthrough of how it works: https://www.youtube.com/watch?v=uc-jdM9XnhE MCPglue lets your agent build its own tools. It…

    2025 · superglue.ai

  24. 24LD

    As I've increasingly pursued orchestrated agentic coding - I needed a safe way to run Claude Code in YOLO mode on my mac. I looked at a lot of options including Docker but then came across Lima (Linux for Mac) and this great guide by Chris Hager on how create a dev sandbox for your mac using Lima. This creates an Ubuntu VM, mapped to your dev directory with RW access, port and SSH forwarding, Mise support for language installs and automatic code agent installs. https://www.metachris.dev/2025/11/sandbox-your-ai-dev-tools-... I followed his guide. Got it working on my…

    Jan 2026 · github.com

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