DataRobot OpenCode: your coding agent, your model choice
There are over 70 coding agents on the market: Claude Code, Codex, Cursor, Copilot, Devin, and a long tail of smaller entrants showing up in engineers’ newsfeeds every week. Someone runs a benchmark, posts the leaderboard, and by the end of the week, half the org wants to try whatever is in first place. The pace behind that impulse is real: these tools are improving every few weeks.
The problem is what “trying a new model” actually costs. Claude Code only runs Anthropic’s models. Codex only runs OpenAI’s. Pick one and you’re locked into the model provider that comes with it.
If you want to try a different model, such as something open-weight and less expensive for a given task, you’re not just changing a setting. You’re switching the whole tool. Chasing a model, price point, or benchmark means adopting a new coding agent, and a new vendor.
In organizations, that’s where the review shows up. Every new coding agent presents the same three questions:
Does it train on your code by default?
Where does inference physically run?
Is pricing per seat or per token?
The answers change tool to tool, but the review itself is nearly identical every time, and legal, security, and finance end up doing it from scratch each time.
To bridge this gap, DataRobot OpenCode delivers a state-of-the-art coding agent that supports model choice across closed, open, and bring-your-own options, all while maintaining rigorous governance.
Getting started only takes a few minutes.
How DataRobot OpenCode works
DataRobot OpenCode runs on the DataRobot LLM Gateway, the same governed entry point already used for every model on the platform, so the agent inherits that governance instead of routing around it.
All of it sits behind one already-approved key. Switching from a closed frontier model to an open-weight one for a cost-sensitive task is a config change, not a new vendor relationship.
DataRobot agent skills, including Agent Assist, come preinstalled, so OpenCode is enterprise-ready on day one, not just model-flexible. That’s the same skills layer DataRobot ships for Cursor, Claude Code, and Gemini, applied here to an agent that isn’t tied to any single vendor’s models.
Installation is three commands from the DataRobot CLI. No separate API key to request, no model configuration to write by hand.
You can install and launch OpenCode in your terminal or run it from the DataRobot UI:
brew install datarobot-oss/taps/dr-cli
# installs the DataRobot CLI in your terminal; not needed inside the DataRobot UI
dr plugin install opencode
# installs the OpenCode plugin
dr opencode
# launches OpenCode, already wired to the Gateway with DataRobot skills
Pick a model from the LLM Gateway via:
/models
Then, launch Agent Assist to use natural language to design, test, build, and deploy production-grade agents:
dr assist
Try it
Get started today. Run the following commands in your terminal:
brew install datarobot-oss/taps/dr-cli
dr plugin install opencode
dr opencode
Build: Create your first DataRobot Agent
Learn more: DataRobot Skills, MCP, and the agentic developer surface
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