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![ui](https://github.com/user-attachments/assets/fdf0679f-b107-48ce-b326-04db752838d9) <img width="1409" height="605" alt="Work knowledge graph" src="https://github.com/user-attachments/assets/707d0452-459d-4710-be85-b5322b433151" />
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<a href="https://discord.gg/rxB8pzHxaS" target="_blank" rel="noopener"> <a href="https://www.rowboatlabs.com/" target="_blank" rel="noopener">
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# RowboatX - Claude Code for Everyday Automations # Rowboat
**An open-source, local-first AI coworker with memory for everyday work**
</h5> </h5>
RowboatX is a local-first CLI for creating background AI agents with full shell access. Rowboat connects your email and meeting notes, builds long-lived knowledge from them, and uses that knowledge to help get work done on your machine.
**Example agents you can create:**
- Research every person before your meetings (Exa search MCP + Google Calendar MCP)
- Daily podcast summarizing your saved articles (ElevenLabs MCP + ffmpeg)
- Auto-triage Slack DMs and draft responses while you sleep (Slack MCP)
## Quick start
```bash
npx @rowboatlabs/rowboatx@latest
```
## Demo
[![Screenshot](https://github.com/user-attachments/assets/ab46ff8b-44bd-400e-beb0-801c6431033f)](https://www.youtube.com/watch?v=cyPBinQzicY&t)
## Examples
### Add and Manage MCP servers
`$ rowboatx`
- Add MCP: 'Add this MCP server config: \<config\> '
- Explore tools: 'What tools are there in \<server-name\> '
### Create background agents
`$ rowboatx`
- 'Create agent to do X.'
- '... Attach the correct tools from \<mcp-server-name\> to the agent'
- '... Allow the agent to run shell commands including ffmpeg'
### Schedule and monitor agents
`$ rowboatx`
- 'Make agent \<background-agent-name\> run every day at 10 AM'
- 'What agents do I have scheduled to run and at what times'
- 'When was \<background-agent-name\> last run'
- 'Are any agents waiting for my input or confirmation'
### Run background agents manually
``` bash
rowboatx --agent=<agent-name> --input="xyz" --no-interactive=true
```
```bash
rowboatx --agent=<agent-name> --run_id=<run_id> # resume from a previous run
```
## Models support
You can configure your models using:
```bash
rowboatx model-config
```
Alternatively, you can directly edit `~/.rowboat/config/models.json`
```json
{
"providers": {
"openai": {
"flavor": "openai"
},
"lm-studio": {
"flavor": "openai-compatible",
"baseURL": "http://localhost:2000/...",
"apiKey": "...",
"headers": {
"foo": "bar"
}
},
"anthropic": {
"flavor": "anthropic"
},
"google": {
"flavor": "google"
},
"ollama": {
"flavor": "ollama"
}
},
"defaults": {
"provider": "lm-studio",
"model": "gpt-5"
}
}
```
## Contributing
We want help with:
- **Agent templates** - Pre-built agents others can use (podcast generator, meeting prep, etc.)
- **MCP server integrations** - Add support for new tools
- **Platform support** - Windows improvements, Linux edge cases
```bash
git clone git@github.com:rowboatlabs/rowboat.git
cd rowboat
npm install
npm run build
npm link
rowboatx
```
Ping us on [Discord](https://discord.com/invite/rxB8pzHxaS) if you want to discuss before building.
--- ---
## Prefer a Web UI: Rowboat Studio
*Cursor for Multi-agent Workflows* ## Demo
⚡ Build AI agents instantly with natural language | 🔌 Connect tools with one-click integrations | 📂 Power with knowledge by adding documents for RAG | 🔄 Automate workflows by setting up triggers and actions | 🚀 Deploy anywhere via API or SDK<br><br> [![Demo video](https://github.com/user-attachments/assets/f378285b-4ef3-4a4b-aa20-7dbb664e496c)](https://www.youtube.com/watch?v=T2Bmiy05FrI)
### Quick start ---
1. Set your OpenAI key
```bash
export OPENAI_API_KEY=your-openai-api-key
```
2. Clone the repository and start Rowboat (requires Docker) ## Quick start
```bash
./start.sh
```
3. Access the app at [http://localhost:3000](http://localhost:3000). **Download for Mac:**
#### Create a multi-agent assistant with MCP tools by chatting with Rowboat https://github.com/rowboatlabs/rowboat/releases/latest
[![meeting-prep](https://github.com/user-attachments/assets/c8a41622-8e0e-459f-becb-767503489866)](https://youtu.be/KZTP4xZM2DY)
See [Docs](https://docs.rowboatlabs.com/) for more details. ## What it does
Rowboat ingests your:
- **Email** (Gmail)
- **Meeting notes** (Granola, Fireflies)
and organizes them into a local, Obsidian-compatible vault of plain Markdown files with backlinks.
This vault is not just for browsing or search. It becomes a working memory that Rowboats AI uses to take actions on your behalf.
As new emails and meetings come in, the relevant notes update automatically, building persistent context across people, projects, organizations, and topics.
---
## How its different
Most AI tools reconstruct context on demand by searching transcripts or documents.
Rowboat maintains **long-lived knowledge** instead:
- context accumulates over time
- relationships are explicit and inspectable
- notes are editable by you, not hidden inside a model
- everything lives on your machine as plain Markdown
The result is memory that compounds, rather than retrieval that starts cold every time.
---
## What you can do with it
Rowboat uses this knowledge to help with everyday work, including:
- Drafting emails using accumulated context
- Preparing for meetings from prior decisions and discussions
- Organizing files and project artifacts as work evolves
- Running shell commands or scripts as agent actions
- Extending capabilities via external tools and MCP servers
Actions are explicit and grounded in the current state of your knowledge.
---
## Local-first by design
- All data is stored locally as plain Markdown
- No proprietary formats or hosted lock-in
- Works with local models via Ollama or LM Studio, or hosted models if you prefer
- You can inspect, edit, back up, or delete everything at any time
--- ---
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Made with ❤️ by the Rowboat team Made with ❤️ by the Rowboat team
[Discord](https://discord.gg/rxB8pzHxaS) · [Twitter](https://x.com/intent/user?screen_name=rowboatlabshq) [Discord](https://discord.com/invite/htdKpBZF) · [Twitter](https://x.com/intent/user?screen_name=rowboatlabshq)
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