# rowboat
**Repository Path**: ailist/rowboat
## Basic Information
- **Project Name**: rowboat
- **Description**: Rowboat 是一款低代码 AI IDE，用于构建连接多智能体助手的 MCP 工具。Rowboat Copilot 会根据你的需求为您构建智能体，并且你也可以选择手动完成所有操作
- **Primary Language**: TypeScript
- **License**: Apache-2.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-04-24
- **Last Updated**: 2025-06-22
## Categories & Tags
**Categories**: Uncategorized
**Tags**: None
## README
Let AI build multi-agent workflows for you in minutes
- ✨ **Start from an idea -> copilot builds your multi-agent workflows**
- E.g. "Build me an assistant for a food delivery company to handle delivery status and missing items. Include the necessary tools."
- 🌐 **Connect MCP servers**
- Add the MCP servers in settings -> import the tools into Rowboat.
- 📞 **Integrate into your app using the HTTP API or Python SDK**
- Grab the project ID and generated API key from settings and use the API.
Powered by OpenAI's Agents SDK, Rowboat is the fastest way to build multi-agents!
## Quick start
1. Set your OpenAI key
```bash
export OPENAI_API_KEY=your-openai-api-key
```
2. Clone the repository and start Rowboat
```bash
git clone git@github.com:rowboatlabs/rowboat.git
cd rowboat
./start.sh
```
3. Access the app at [http://localhost:3000](http://localhost:3000).
Note: We have added native RAG support including file-uploads and URL scraping. See the [RAG](https://docs.rowboatlabs.com/using_rag) section of our docs for this.
Note: See the [Using custom LLM providers](https://docs.rowboatlabs.com/setup/#using-custom-llm-providers) section of our docs for using custom providers like OpenRouter and LiteLLM.
## Demo
#### Create a multi-agent assistant with MCP tools by chatting with Rowboat
[](https://youtu.be/YRTCw9UHRbU)
## Integrate with Rowboat agents
There are 2 ways to integrate with the agents you create in Rowboat
1. HTTP API
- You can use the API directly at [http://localhost:3000/api/v1/](http://localhost:3000/api/v1/)
- See [API Docs](https://docs.rowboatlabs.com/using_the_api/) for details
```bash
curl --location 'http://localhost:3000/api/v1//chat' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer ' \
--data '{
"messages": [
{
"role": "user",
"content": "tell me the weather in london in metric units"
}
],
"state": null
}'
```
2. Python SDK
You can use the included Python SDK to interact with the Agents
```
pip install rowboat
```
See [SDK Docs](https://docs.rowboatlabs.com/using_the_sdk/) for details. Here is a quick example:
```python
from rowboat import Client, StatefulChat
from rowboat.schema import UserMessage, SystemMessage
# Initialize the client
client = Client(
host="http://localhost:3000",
project_id="",
api_key=""
)
# Create a stateful chat session (recommended)
chat = StatefulChat(client)
response = chat.run("What's the weather in London?")
print(response)
# Or use the low-level client API
messages = [
SystemMessage(role='system', content="You are a helpful assistant"),
UserMessage(role='user', content="Hello, how are you?")
]
# Get response
response = client.chat(messages=messages)
print(response.messages[-1].content)
```
Refer to [Docs](https://docs.rowboatlabs.com/) to learn how to start building agents with Rowboat.