dsh-superagent vs OpenHands
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
A research prototype of a coding agent that watches one GitHub repo and acts when asked.
Open source · MIT
A self-hosted control panel that runs AI coding agents on your machine, in Docker, or in the cloud.
The short answer
Choose dsh-superagent if you need…
- Engineering teams exploring autonomous coding agents on a single GitHub repository
- Developers studying how agent work items, authorization and a review panel can fit together
- Researchers reading the accompanying design article alongside working code
- Operators who want an agent to act only when a team rule or a person allows it
Choose OpenHands if you need…
- Developers who want coding agents running on a server while their laptop is off
- Teams that want a shared agent server for tasks like code review or dependency updates
- People who want to connect agents to Slack, GitHub, or Linear through automations
- Users who want to choose their own LLM provider
Side-by-side
| dsh-superagent | OpenHands | |
|---|---|---|
| Type | AI model / agent | App |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 11k | 92.5k |
| Setup difficulty | Advanced | Intermediate |
| How you get it | Clone and build from source | Install with a package manager |
| Main language | TypeScript | TypeScript |
| Last code update | 6 days ago | 4 days ago |
What each one is
dsh-superagent
dsh-superagent is a proactive coding agent built for one GitHub repository, packaged as a bundle for DeepSeek Harness. It listens to GitHub and optionally Feishu; when an allowed person asks for work, it opens a work item, works on it in its own session and directory, and replies in the original conversation, for example with a pull request. A web panel shows what needs a person's attention. The README describes it as a research prototype, not an official DeepSeek product, and not production-ready.
OpenHands
Agent Canvas is a self-hosted control center for AI coding agents. You start conversations with agents and set up automations, such as generating reports that publish to Slack or breaking GitHub issues into tasks. It runs on your own machine by default and can also connect to agents running in Docker, on virtual machines, or on OpenHands Cloud or Enterprise infrastructure. It can run the open source OpenHands agent or third-party agents such as Claude Code, Codex, and Gemini CLI.
Best for
dsh-superagent
- Engineering teams exploring autonomous coding agents on a single GitHub repository
- Developers studying how agent work items, authorization and a review panel can fit together
- Researchers reading the accompanying design article alongside working code
- Operators who want an agent to act only when a team rule or a person allows it
OpenHands
- Developers who want coding agents running on a server while their laptop is off
- Teams that want a shared agent server for tasks like code review or dependency updates
- People who want to connect agents to Slack, GitHub, or Linear through automations
- Users who want to choose their own LLM provider
Strengths
dsh-superagent
- Clear stated philosophy of minimizing human attention, documented in docs/000-philosophy.md
- Ordered documentation set covering domain model, authorization, execution, prompts and architecture
- Uses the MIT license, which permits reuse with few conditions
OpenHands
- Self-hosted, so you control where agents run and where your work is stored
- Supports several agents and backends from one frontend
- Released under the MIT license with a large public community (about 92,000 stars)
Not ideal for
dsh-superagent
- Teams needing production-ready software, since the README warns it may contain bugs and inconsistent practices
- Anyone wanting a simple install in minutes, since the README says setup has many steps and recommends an agent-guided setup
- Users who need features described in the article, since the README says some designs are not implemented in this prototype
OpenHands
- People who need strong isolation by default: the quickstart without a sandbox gives the agent full access to your filesystem
- Non-technical users who are not comfortable with Node.js, npm, Docker, or the command line
- Anyone who needs a fully hosted service with no setup, since the README centers on self-hosting
Trade-offs
dsh-superagent
- The README explicitly labels it research code that should be reviewed and adapted before use
- The README says it is not identical to the internal version or the article's implementation
- Setup has many steps and the full install details are not included in the truncated README
OpenHands
- Running without a sandbox gives the agent full access to your filesystem, so the Docker options need careful setup
- Multiple features depend on configuring backends, LLM keys, and integrations, which takes effort
- The README is truncated and does not fully document security hardening or every integration; see the linked docs
Getting started
dsh-superagent
Clone the repository
git clone https://github.com/deepseek-ai/dsh-superagent-prototypeRun the project checks (typecheck, tests, build)
pnpm checkOpenHands
Install globally with npm (no sandbox)
npm install -g @openhands/agent-canvasStart the full local stack
agent-canvasFrequently asked questions
What is the difference between dsh-superagent and OpenHands?
dsh-superagent: A research prototype of a coding agent that watches one GitHub repo and acts when asked. OpenHands: A self-hosted control panel that runs AI coding agents on your machine, in Docker, or in the cloud. dsh-superagent suits engineering teams exploring autonomous coding agents on a single github repository, while OpenHands suits developers who want coding agents running on a server while their laptop is off.
Are dsh-superagent and OpenHands free?
dsh-superagent: Free and open source. OpenHands: Free and open source.
Which is easier to set up, dsh-superagent or OpenHands?
OpenHands is easier to get started with (rated intermediate); dsh-superagent is rated advanced and usually needs more setup.
Is dsh-superagent or OpenHands more popular?
OpenHands has more GitHub stars (92.5k) than dsh-superagent (11k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to dsh-superagent and OpenHands?
Other options people compare them with include SWE-agent, One API, LlamaGPT, codex-chatgpt-web, wechat-bot.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.