Show HN: RowboatX – open-source Claude Code for everyday automations
github.comClaude Code is great, but it’s focused on coding. The missing piece is a native way to build and run custom background agents for non-code tasks. We built RowboatX as a CLI tool modeled after Claude Code that lets you do that. It uses the file system and unix tools to create and monitor background agents for everyday tasks, connect them to any MCP server for tools, and reason over their outputs.
Because RowboatX runs locally with shell access, the agents can install tools, execute code, and automate anything you could do in a terminal with your explicit permission. It works with any compatible LLM, including open-source ones.
Our repo is https://github.com/rowboatlabs/rowboat, and there’s a demo video here: https://youtu.be/cyPBinQzicY
For example, you can connect RowboatX to the ElevenLabs MCP server and create a background workflow that produces a NotebookLM-style podcast every day from recent AI-agent papers on arXiv. Or you can connect it to Google Calendar and Exa Search to research meeting attendees and generate briefs before each event.
You can try these with: `npx @rowboatlabs/rowboatx`
We combined three simple ideas:
1. File system as state: Each agent’s instruction, memory, logs, and data are just files on disk, grepable, diffable, and local. For instance, you can just run: grep -rl '"agent":"<agent-name>"' ~/.rowboat/runs to list every run for a particular workflow.
2. The supervisor agent: A Claude Code style agent that can create and run background agents. It predominantly uses Unix commands to monitor, update, and schedule agents. LLMs handle Unix tools better than backend APIs [1][2], so we leaned into that. It can also probe any MCP server and attach the tools to the agents.
3. Human-in-the-loop: Each background agent can emit a human_request message when needed (e.g. drafting a tricky email or installing a tool) that pauses execution and waits for input before continuing. The supervisor coordinates this.
I started my career over a decade ago building spam detection models at Twitter, spending a lot of my time in the terminal with Unix commands for data analysis [0] and Vowpal Wabbit for modeling. When Claude Code came along, it felt familiar and amazing to work with. But trying to use it beyond code always felt a bit forced. We built RowboatX to bring that same workflow to everyday tasks. It is Apache-2.0 licensed and easily extendable.
While there are many agent builders, running on the user's terminal enables unique use cases like computer and browser automation that cloud-based tools can't match. This power requires careful safety design. We implemented command-level allow/deny lists, with containerization coming next. We’ve tried to design for safety from day one, but we’d love to hear the community’s perspective on what additional safeguards or approaches you’d consider important here.
We’re excited to share RowboatX with everyone here. We’d love to hear your thoughts and welcome contributions!
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[0] https://web.stanford.edu/class/cs124/kwc-unix-for-poets.pdf [1] https://arxiv.org/pdf/2405.06807 [2] https://arxiv.org/pdf/2501.10132
One of the main reasons for me for sticking with Claude Code (also for non-coding tasks, I think the name is a misnomer) is the fixed price plan. Pretty much any other open-source alternative requires API key, which means that as soon as I start using it _for real_, I'll start overpaying and/or hitting limits too fast. At least that was my initial experience with API from OpenAI/Claude/Gemini.
Am I biased/wrong here?
Yep, this is a fair take. Token usage shoots up fast when you do agentic stuff for coding. I too end up doing the same thing.
But for most background automations your might actually run, the token usage is way lower and probably an order of magnitude cheaper than agentic coding. And a lot of these tasks run well on cheaper models or even open-source ones.
So I don't think you are wrong at all. It is just that I believe the expensive token pattern mostly comes from coding-style workloads.
I don't doubt you, but it would be interesting to see some token usage measurements for various tasks like you describe.
For example, the NotebookLM-style podcast generator workflow in our demo uses around 3k tokens end to end. Using Claude Sonnet 4.5’s blended rate (about $4.5 per million tokens for typical input/output mix), you can run this every day for roughly eight months for a bit over three dollars. Most non-coding automations end up in this same low range.
What non coding tasks do you use Claude Code for? Genuinely curious.
LOTS! Sometimes for quick file system organization, creating Claude skills, deep document analysis.
Anthropic published a doc or two about this too, here's one of them: https://www-cdn.anthropic.com/58284b19e702b49db9302d5b6f135a...
Ah, that’s interesting. Are there any parts of Claude Code that you feel could work differently or get in your way for these kinds of tasks?
It can also take notes, write down plans and TODO lists, update on gym records, etc, etc.
Curious how you're handling notes and TODO lists. Do you give Claude Code access to a local markdown file, or is it working some other way?
You're not wrong, though I suspect the AI "bubble burst" begins to happen when companies like Anthropic stop giving us so much compute for 'free' the only hope is that as things get better their cheaper models get as good as their best models today and so it costs drastically less to use them.
Sonnet is 3$ per million tokens, Grok Code Fast is 0.2$. IME the latter is better for me. Wish everybody treats AI as a pay-as-you-go commodity instead of getting dependant on rugpulls. My stack is Openrouter (model marketplace) and Aider (Kilocode and Cline for user friendly alternatives).
Zed is nicely setup for this I just have not taken the time. I do like how Claude works atm. The coding agent functionality is what's nice about Claude Code. I don't know that Grok Code Fast has that?
Came across this interesting article on the internals of Claude Code: https://medium.com/@outsightai/peeking-under-the-hood-of-cla... . The author redirected the LLM calls into LiteLLM to analyze how it behaves.
That's really neat!
Will check out Grok Code Fast - thanks for the pointer. In my experience, coding agents can swing a lot in quality depending on the model’s reasoning power. When the model starts making small but avoidable mistakes, the overhead tends to cancel out the benefit. Curious to see how Grok performs on multi-step coding tasks.
True. Im working with Python CRUD apps, which every model is fluent in. And I'm personally generating 100-line changes, not letting it run while I'm AFK.
Ah, that makes sense. I’ve had similar luck with UI refactoring on cheaper models, mainly because you can quickly verify whether the output is right.
That's what I love most about Claude. I love Django and I love React (the richness of building UIs with React is insane) and sure enough Claude Code (and other models I'm sure) is insanely good at both.
Yeah, I think when they made the bet it genuinely made sense. But in coding workflows, once models got cheaper, people did not spend less. They just started packing way more LLM calls into a single turn to handle complex agentic coding steps. That is probably where the math started to break down.
I'm increasingly seeing code-adjacent people who are using coding agents for non-coding things because the tooling support it better, and the agents work really well.
It's an interesting area, and glad to see someone working on this.
The other program in the space that I'm aware of is Block's Goose.
Yep, totally agree. We actually had an earlier web version, and the big learning was that without access to code-related tools the agent feels pretty limited. That pushed us toward a CLI where it can use the full shell and behave more like a real worker.
Really appreciate the support and the Goose pointer. Would love to hear what you think of RowboatX once you try it.
> E.g. "Generate a NotebookLM-style podcast from my saved articles every morning"
How does it do that? Does it require a tool for that? Or a special model?
In the demo - for the voice and music, it uses the ElevenLabs MCP server for TTS, and ffmpeg locally to stitch the audio together. In the demo we pull content from Tweets via an MCP tool, but you can swap that step for anything — for example, fetching your saved articles with curl. There’s no special model required; any LLM that can call tools will work.
We’ve included the exact agents used in the demo here for reference: https://github.com/rowboatlabs/rowboat/blob/cli/apps/cli/exa....
We’re adding an easier way to run examples soon. In the meantime, if you’d like to try this one locally: (1) Copy the agent file into ~/.rowboat/agents/ (2) Add the MCP server (and your keys) to ~/.rowboat/config/mcp.json (3) Run: 'rowboatx --agent=tweet-podcast --input=go'
Pretty cool! A bit of an upgrade of just letting claude write pocketflow agents for stuff. That's what I'm doing now.
Thanks! Curious what kinds of workflows you are automating right now and any pain points you’ve run into.
I automated a bunch of business workflows like sorting documents for accounting in my cloud storage, tagging emails that are invoices, stuff like that. I do this for a living though, so I also use these as casestudies and rowboat is a hard sell for end users I guess.
Thanks, that makes sense. I assume the CLI approach might be the main hurdle for end users?
Exactly. They want something that just works and runs somewhere. I'm talking about SME owners.
Can this use local LLMs?
Yes - you can use local LLMs through LiteLLM and Ollama. Would you like us to support anything else?
LM Studio?
Yes, because LM Studio is openai-compatible. When you run rowboatx the first time, it creates a ~/.rowboat/config/models.json. You can then configure LM Studio there. Here is an example: https://gist.github.com/ramnique/9e4b783f41cecf0fcc8d92b277d...
I wonder how this compares with the CLine CLI?
Cline is great, but it’s primarily focused on coding workflows, similar to Claude Code. RowboatX is aimed at a different category: background agents for non-coding automations (e.g. meeting prep, daily briefings, etc).
The big difference from Claude Code (and Cline) is that RowboatX can spin up persistent background agents that run on schedules, use the system shell, and call MCP tools to automate tasks outside of coding.
Open source... "enter OpenAI API key"... closes tab
Saw comment about local LLM support that I somehow totally missed. Re-opening tab. Should have led with that!
Ah did not realize this - good to know!
Fixed the quick start instructions to not start with OpenAI.