Show HN: Rowboat – AI coworker that turns your work into a knowledge graph (OSS)
95 points - today at 4:47 PM
Hi HN,
AI agents that can run tools on your machine are powerful for knowledge work, but they’re only as useful as the context they have. Rowboat is an open-source, local-first app that turns your work into a living knowledge graph (stored as plain Markdown with backlinks) and uses it to accomplish tasks on your computer.
For example, you can say "Build me a deck about our next quarter roadmap." Rowboat pulls priorities and commitments from your graph, loads a presentation skill, and exports a PDF.
Our repo is https://github.com/rowboatlabs/rowboat, and there’s a demo video here: https://www.youtube.com/watch?v=5AWoGo-L16I
Rowboat has two parts:
(1) A living context graph: Rowboat connects to sources like Gmail and meeting notes like Granola and Fireflies, extracts decisions, commitments, deadlines, and relationships, and writes them locally as linked and editable Markdown files (Obsidian-style), organized around people, projects, and topics. As new conversations happen (including voice memos), related notes update automatically. If a deadline changes in a standup, it links back to the original commitment and updates it.
(2) A local assistant: On top of that graph, Rowboat includes an agent with local shell access and MCP support, so it can use your existing context to actually do work on your machine. It can act on demand or run scheduled background tasks. Example: “Prep me for my meeting with John and create a short voice brief.” It pulls relevant context from your graph and can generate an audio note via an MCP tool like ElevenLabs.
Why not just search transcripts? Passing gigabytes of email, docs, and calls directly to an AI agent is slow and lossy. And search only answers the questions you think to ask. A system that accumulates context over time can track decisions, commitments, and relationships across conversations, and surface patterns you didn't know to look for.
Rowboat is Apache-2.0 licensed, works with any LLM (including local ones), and stores all data locally as Markdown you can read, edit, or delete at any time.
Our previous startup was acquired by Coinbase, where part of my work involved graph neural networks. We're excited to be working with graph-based systems again. Work memory feels like the missing layer for agents.
We’d love to hear your thoughts and welcome contributions!
Comments
In practice, i connected gmail and asked it: "can you archive emails that have an unsubscribe link in them (that are not currently archived)?" and it got stuck on "I'll check what MCP tools are available for email operations first." But i connected gmail through your interface, and I don't see in settings anything about it also having configured the mcp? I also looked at the knowledge graph and it had 20 entities, NONE of which I had any idea what they were. I'm guessing its just putting in people trying to spam me into the contacts? It didn't finish running, but I didn't want to burn endless tokens trying to see if it would find actual people i care about, so I shut it down. One "proxy" for "people i care about" might be "people I send emails to"? I could see how this is a hard problem. I also think regardless I want things more transparent. So for the moment, I'm sticking with Craft Code for this even though it is missing some major things but at least its more clear what it is: its claude code, with a nice UI.
Hope this was helpful. I know there are multiple people working on things in this family, and I will probably be "largely solved" by the end of 2026, and then we will want it to do the next thing! Good luck, I will watch for updates and these are some nice ideas!
Google Mail should not be used, nor its use encouraged. Nor should you encourage the use of LLMs of large corporations which suck in user data for mining, analysis, and surveillance purposes.
I would also be worried about energy use, and would not trust an "agent" to have shell access, that sounds rather unsafe.