How to Use the Dataiku DSS MCP in Cline

Q: Can Cline trigger a Dataiku DSS scenario run?

Yes. Cline uses runscenario to kick off builds and model retraining directly. It can monitor the progress of the run in your VS Code sidebar using getjob.

Q: How does Cline read Dataiku DSS schemas?

Cline invokes datasetschema to pull column details. This lets the agent write accurate local Python or SQL code that aligns with your DSS datasets.

Q: Can I list my Dataiku DSS plugins using Cline?

Yes, Cline uses listplugins to check which custom extensions are installed on your DSS instance. This helps your agent understand what processors are available for your data flows.

Give Cline direct access to your Dataiku DSS projects to build, monitor, and document data pipelines from VS Code.

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Connect Dataiku DSS MCP to Cline

Create your Vinkius account to connect Dataiku DSS to Cline 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 Dataiku DSS with Cline

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Inspect Dataiku DSS schemas directly in Cline

`dataset_schema` exposes the exact column layout and data types of any Dataiku DSS dataset to Cline. Cline uses this tool to instantly understand the structure of your data tables before writing any integration scripts. Instead of switching back and forth to your browser, Cline pulls the schema directly into your editor. You can tell Cline to write a data cleaning script, and it will match your DSS columns exactly on the first try.

Monitor active pipeline jobs from your editor

`list_jobs` retrieves the active training runs and data build tasks in your Dataiku DSS project. Cline invokes this tool alongside `get_job` to watch your remote pipeline executions and report failures directly in your sidebar. This MCP Server lets Cline act as an autonomous operator. If a build fails, Cline reads the job output, identifies the broken recipe, and prepares a fix in your local workspace.

Query DSS configurations with this MCP Server

`get_recipe` retrieves the specific transformation steps and configurations of your Dataiku DSS data flows. Cline uses this tool to audit your data pipelines and write documentation for your team. This MCP server handles the heavy lifting of reading complex JSON recipes and translating them into clear markdown. You get accurate documentation of your DSS flows without writing a single line of it yourself.

Setup guide

Set up Dataiku DSS MCP in Cline

Prerequisites

VS Code with Cline extension installed
Active Vinkius subscription with a valid endpoint token

1

Open Cline MCP settings

Click the Cline icon in the VS Code sidebar to open the Cline panel. Then click the MCP Servers icon (server stack) at the top-right corner of the panel.
2

Add a remote server

Click "Remote Servers" at the top, then click "Add Remote MCP". In the Name field, type dataiku-dss-mcp. In the URL field, paste your Vinkius endpoint: https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp. Get your token from cloud.vinkius.com.
3

Enable the server

After saving, the server appears in the Cline MCP panel. Toggle the switch to enable it. The status indicator turns green when the connection is live.
4

Start using tools

Return to the Cline chat and ask: "Check my latest Dataiku DSS refund status." Cline will discover the available tools and request your approval before invoking each one — giving you full control over every action.

Cline MCP Settings

{
  "mcpServers": {
    "dataiku-dss-mcp": {
      "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    }
  }
}

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Common questions about Dataiku DSS MCP in Cline

Yes. Cline uses `run_scenario` to kick off builds and model retraining directly. It can monitor the progress of the run in your VS Code sidebar using `get_job`.

Cline invokes `dataset_schema` to pull column details. This lets the agent write accurate local Python or SQL code that aligns with your DSS datasets.

Yes, Cline uses `list_plugins` to check which custom extensions are installed on your DSS instance. This helps your agent understand what processors are available for your data flows.

Open the Cline sidebar and click the MCP Servers icon. You can add the server using the Remote Servers tab or by editing `cline_mcp_settings.json` directly.

The server only accesses DSS metadata, schemas, and job statuses. Your raw database records and proprietary machine learning model weights stay secure inside your DSS infrastructure.

Use it with your favorite AI tools

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