How to Use the DataRobot MCP in Claude Code

Q: How do I install the DataRobot MCP Server in Claude Code?

Run the claude mcp add command with the HTTP transport flag and your server URL. This adds the configuration directly to your /.claude.json file.

Q: Can I use Claude Code to automate DataRobot project checks?

Yes, you can pipe the output of listprojects into shell scripts. Claude Code runs these commands headlessly in your CI/CD pipelines.

Q: How does Claude Code handle DataRobot datasets?

It queries the listdatasets tool to check your active training files. Your agent can then compare this list with local data directories in your terminal.

Control your DataRobot AutoML pipelines and monitor active deployments directly from your terminal using Claude Code and this MCP server.

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Create your Vinkius account to connect DataRobot to Claude Code and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup DataRobot with Claude Code

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Command-Line AutoML Project Tracking

The `list_projects` and `get_project` tools provide instant terminal access to your active DataRobot experiments. Claude Code runs these tools to verify the status of long-running training jobs without opening a browser. You can pipe this project data directly into local shell scripts or cron jobs. This makes it easy to build automated alerts that trigger when a training run completes.

Audit ML Datasets via CLI MCP Server

The `list_datasets` tool exposes all training files stored in your DataRobot account to your shell environment. Claude Code checks this list to confirm that your automated CI/CD pipelines are using the latest data versions. If a dataset version is outdated, your agent alerts you in the terminal. You can then run a quick shell command to update your data pipeline config.

Monitor Production Deployments

The `list_deployments`, `list_models`, and `get_model` tools let you query live endpoints and model metrics from the command line. Claude Code uses these tools to check for model degradation or high latency in your production systems. SREs and DevOps engineers can write terminal scripts that auto-scale or roll back deployments based on these real-time metrics. You get total visibility over your production ML stack without complex setups.

Setup guide

Set up DataRobot MCP in Claude Code

Prerequisites

Claude Code CLI installed (npm install -g @anthropic-ai/claude-code)
Active Vinkius subscription with a valid endpoint token

1

Run the add command

Open your terminal and run the command shown on the right. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com. Use --scope user to make it available across all projects.
2

Verify the connection

Start a Claude Code session and type /mcp to list connected servers. You should see datarobot-mcp with a green status indicator.
3

Start using tools

Ask Claude Code something like "Check my latest DataRobot transactions." It will automatically discover and invoke the available DataRobot tools.

Terminal

claude mcp add --transport http datarobot-mcp https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

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Prerequisites

Claude Code CLI installed
Active Vinkius subscription with a valid endpoint token

1

Open the config file

Create or edit .mcp.json in your project root for project-level scope, or ~/.claude.json for user-level scope.
2

Add the DataRobot MCP

Paste the JSON snippet shown on the right into the mcpServers object. Replace [YOUR_TOKEN_HERE] with your endpoint token from cloud.vinkius.com.
3

Restart Claude Code

Start a new Claude Code session. Type /mcp to confirm the server is connected. The tools will be automatically available in your conversation.

.mcp.json

{
  "mcpServers": {
    "datarobot-mcp": {
      "type": "url",
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DataRobot. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about DataRobot MCP in Claude Code

Run the `claude mcp add` command with the HTTP transport flag and your server URL. This adds the configuration directly to your `~/.claude.json` file.

Yes, you can pipe the output of `list_projects` into shell scripts. Claude Code runs these commands headlessly in your CI/CD pipelines.

It queries the `list_datasets` tool to check your active training files. Your agent can then compare this list with local data directories in your terminal.

The server supports stdio, HTTP, and SSE transports. You can configure these options directly when adding the tool via the CLI.

Every request runs through a secure, single-tenant V8 isolate sandbox on the Vinkius MCP platform. Your deployment logs and performance scores are never cached or exposed to external networks.

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