[HN Gopher] Show HN: RowboatX - open-source Claude Code for ever...
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       Show HN: RowboatX - open-source Claude Code for everyday
       automations
        
       Claude 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!  --  [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
        
       Author : segmenta
       Score  : 38 points
       Date   : 2025-11-18 18:50 UTC (4 hours ago)
        
 (HTM) web link (github.com)
 (TXT) w3m dump (github.com)
        
       | jckahn wrote:
       | Can this use local LLMs?
        
         | segmenta wrote:
         | Yes - you can use local LLMs through LiteLLM and Ollama. Would
         | you like us to support anything else?
        
           | thedangler wrote:
           | LM Studio?
        
             | ramnique wrote:
             | 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/r
             | amnique/9e4b783f41cecf0fcc8d92b277d...
        
       | divan wrote:
       | 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?
        
         | segmenta wrote:
         | 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.
        
       | nl wrote:
       | 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.
        
         | segmenta wrote:
         | 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.
        
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       (page generated 2025-11-18 23:00 UTC)