Artifact Server is an open source alternative to Claude Code Artifacts; enabling teams to own, share, and collaborate on artifacts throughout the development lifecycle.
It runs locally, deploys to Cloudflare, GCP, AWS, or anywhere Kubernetes. It also creates live feedback loops with agents like Pi and Claude via MCP channels.
Why
There are questions I don't like having to ask when using Claude:
- Why am I going to a claude[dot]ai domain to look at my local development artifacts?
- Why are contractors sending me paid work in a claude[dot]ai link on their account?
- Why can I not easily persist, version, and share these artifacts with my team and other agents?
Anyway, artifacts are good (and the CC team has done a great job evangelizing HTML and cool workflows around it). They are becoming a substantial part of the development process and teams need more ownership & collaborative capabilities.
Artifact Server creates a collaboration surface for human-to-human review, integrated AI feedback, and versioning. I can tag Pi in an artifact comment and that comment will queue immediately in Pi (no polling!).
I also think Git is the right memory layer for artifacts. Having provenance of what changed and why is useful esp for multi-agent workflows. Versioned artifacts are a key feature along with the sharing/collaboration features.
I bought the game so I could study the code. Unfortunately it is wasm & obfuscated. I'm gonna see what my handy dandy big giant brain buddies can do with it.
Two things: (1) models are far more autonomous and run for longer coherently, (2) visibility into the development process was lost in local development.
Because models run for a long time autonomously developers need to manage more agents simultaneously. At that point you basically need a tracker for tasks in flux, and compute for each agent. It also means that the interactive monitoring isn’t as helpful anymore.
Regarding visibility, developers now think in high level architecture rather than lines of code, but implementation details are still important to document. We also want to understand when agents are hitting pain points. Both of these basically require archiving agent outputs more deeply than just code changes and commits.
I see. What would the proper solution then look like for when we should consider moving our teams? Sounds like you you said they're all current ones are missing ergonomics. Do you think it's slack code?
I created /bro a couple model iterations prior. I use it everyday many times a day and it's getting worse. I was actually using it more with GPT models but they have been getting better.
"It reads the screen, not the DOM", but is built completely on Playwright? At first it made me think you have some visual model at play, but doesn't actually seem that way.
Physical custody of our work is going to be an important discussion for industry. ie where does your code live and how do you access it?
Every agent platform is moving toward you living with them, logging into them, working on their remote computers, only accessing your code and product artifacts with them. This is the caveat we will see with full push-to-cloud swing early on.
Maybe agentic no-code is the natural evolution but this push is happening too early and naively imo. It all feels wrong and I hope industry remains as dissatisfied with this type of lock-in as we’ve always been.
https://github.com/plannotator/artifact-server
https://artifactserver.com
It runs locally, deploys to Cloudflare, GCP, AWS, or anywhere Kubernetes. It also creates live feedback loops with agents like Pi and Claude via MCP channels.
Why
There are questions I don't like having to ask when using Claude:
Anyway, artifacts are good (and the CC team has done a great job evangelizing HTML and cool workflows around it). They are becoming a substantial part of the development process and teams need more ownership & collaborative capabilities.Artifact Server creates a collaboration surface for human-to-human review, integrated AI feedback, and versioning. I can tag Pi in an artifact comment and that comment will queue immediately in Pi (no polling!).
I also think Git is the right memory layer for artifacts. Having provenance of what changed and why is useful esp for multi-agent workflows. Versioned artifacts are a key feature along with the sharing/collaboration features.
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