rowboat
Basic Information
Rowboat is an application and framework for quickly creating, running, and integrating multi-agent AI workflows. It lets users describe an idea in natural language and the built-in copilot scaffolds a multi-agent assistant, including tool selection and orchestration. The project is powered by OpenAI's Agents SDK and supports connecting external MCP servers to import tools. Rowboat can be run locally via provided scripts and environment variables, hosts a web UI for designing and testing agents, and exposes an HTTP API and a Python SDK for embedding created agents into other applications. The README highlights support for retrieval-augmented generation, file uploads, and URL scraping, and notes guidance for using custom LLM providers.
Links
Stars
3444
Github Repository
App Details
Features
Rowboat provides a conversational copilot that generates multi-agent workflows from simple prompts. It integrates MCP servers so external tools can be imported and used by agents. It exposes a documented HTTP API for production integration and a Python SDK for programmatic usage, including stateful chat sessions. Native RAG support is included with file upload and URL scraping for document ingestion. The repo includes a quick start with an environment variable for OpenAI credentials and a start script for local deployment. Additional features shown in the README include support for custom LLM providers, example curl and Python usage, a web UI for creating agents, and documentation and demo assets.
Use Cases
Rowboat streamlines building complex multi-agent assistants by automating workflow construction from high-level ideas, reducing the need to wire agents and tools manually. Teams can prototype assistants in minutes using the UI and copilot, then export project IDs and API keys to integrate agents into apps via HTTP or the Python SDK. Native RAG and scraping support allow agents to use uploaded documents and web content as knowledge sources. Support for external MCP tool servers and custom LLM providers increases extensibility for specialized toolchains. Local deployment via provided scripts enables private testing and development. The README includes examples for chat usage and shows how stateful sessions and low-level API calls work, aiding developer adoption.
-
$$$$ -
$$$$