Vinkius

Dataiku DSS MCP for AI Agents. Manage Enterprise Data Pipelines and Model Monitoring

The Dataiku DSS MCP connects your AI client directly to your entire data science environment. You can list projects, check dataset schemas, monitor complex pipeline jobs, and audit ML model performance without leaving your chat interface. It puts full control of enterprise data workflows right into conversation.

Dataiku DSS MCP for AI Agents MCP is compatible with Claude Claude
Dataiku DSS MCP for AI Agents MCP is compatible with ChatGPT ChatGPT
Dataiku DSS MCP for AI Agents MCP is compatible with Cursor Cursor
Dataiku DSS MCP for AI Agents MCP is compatible with Gemini Gemini
Dataiku DSS MCP for AI Agents MCP is compatible with Windsurf Windsurf
Dataiku DSS MCP for AI Agents MCP is compatible with VS Code VS Code
Dataiku DSS MCP for AI Agents MCP is compatible with JetBrains JetBrains
Dataiku DSS MCP for AI Agents MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

Discover and map projects

List all accessible DSS projects and retrieve detailed structural information about their datasets.

Audit dataset schemas

Get the column names, data types, and full structure for any specified dataset in a project.

Monitor pipeline execution

Track build tasks, training runs, and job status by listing pipeline jobs and analyzing their current state or timing.

Verify data transformation logic

Retrieve the exact configuration structure for recipes—whether they use Python, SQL, or visual tools—to audit data flow.

Control automation scenarios

List available automation scenarios and trigger their execution to securely rebuild pipelines or retrain models.

Review deployed ML models

Identify saved machine learning models and retrieve detailed performance metrics, including the specific trained schema layers.

Audit system connections

List all installed plugins and data source connections (like cloud storage or APIs) to verify organizational access rights.

Waiting for input…

AI Agent
Dataiku DSS MCP for AI Agents

What AI agents can do with 14 Tools for Data Science Workflow Management

Use these tools to control every aspect of your DSS environment, from listing projects to triggering complex data transformations.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using Dataiku DSS MCP

List Projects

Lists all DSS projects that your API key has access to.

Get Project

Retrieves metadata, settings, and tags for a specific Dataiku project.

List Datasets

Lists every dataset contained within a specified project.

Dataset Schema

Provides the complete column names and data types for any given dataset schema.

List Recipes

Lists all defined recipes, which are your data transformation workflows, in a...

List Jobs

Shows all pipeline jobs associated with a project, covering build tasks and model training runs.

Get Job

Gets the current status, timing data, and outputs for a specific job run.

List Scenarios

Retrieves a list of available automation scenarios within a project.

List Models

Lists all machine learning models that have been saved or deployed in the project.

Get Model

Retrieves metadata, algorithm details, and performance metrics for a specific ML...

Run Scenario

Triggers an automation scenario execution, which can rebuild pipelines or retrain...

List Plugins

Lists all DSS plugins that have been installed in the environment.

List Connections

Shows a list of data connections, including configured databases, cloud storage accounts, or APIs.

Get Recipe

Retrieves the full configuration and settings for a specific data transformation...

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

Dataiku DSS MCP for AI Agents MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The Dataiku DSS MCP for AI Agents integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with Dataiku DSS, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
Dataiku DSS MCP for AI Agents MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Dataiku. 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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Sandboxed per request

Zero-Trust Proxy

No stored credentials

DLP Enforced

Policy on each call

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EU data residency

Token Compression

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Dataiku DSS MCP: Auditing Data Pipelines and Recipes

Right now, auditing a data pipeline means jumping between the DSS UI, downloading logs, cross-referencing Python scripts, and manually comparing schema versions across multiple tabs. It's slow, error-prone detective work.

With this MCP, you simply ask your agent to audit the transformation logic. You can use `list_recipes` to see every workflow available and then drill down with `get_recipe` to pull the precise configuration structure into a readable chat format. The painful clicking stops; you get actionable data instantly.

Dataiku DSS MCP: Monitoring ML Model Performance

Previously, checking model health required navigating to the 'Models' tab, finding the specific deployment, and then running a separate performance report. It was a multi-step process just for a status update.

Now, you can ask your agent to list models (`list_models`) and immediately request detailed metrics using `get_model`. You get the algorithm used, the trained schema layers, and key performance indicators right in the chat—no dashboard navigation required.

What Dataiku DSS MCP for AI Agents MCP does for your AI

Need to manage collaborative data science work in a natural way? This MCP lets you talk to your Dataiku DSS instance like it’s an extension of your own brain. Instead of navigating dozens of tabs and clicking through build logs, you just ask your AI agent for what you need—whether that's listing all available projects or checking the precise schema of a raw dataset.

You get immediate status updates on pipeline jobs, monitor training runs, and even trigger automation scenarios to rebuild pipelines when something breaks. It’s full command-line control over data science workflows, accessed via natural language conversation. When you connect this MCP through Vinkius, your agent gets access to the entire catalog of tools needed to manage everything from model metadata to underlying data connections.

Built · Hosted · Managed by Vinkius Dataiku DSS MCP for AI Agents — Data Pipeline Control
Server ID 019d7582-315c-7179-a27e-efc75014bf8f
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about Dataiku DSS MCP for AI Agents MCP

How do I check if my dataiku projects are connected to external databases? +

The MCP allows you to list all data connections and installed plugins. This lets you quickly audit your entire environment by seeing which cloud storage, APIs, or SQL databases are linked to your DSS instance.

Can this MCP help me monitor if a model is performing well? +

Yes, you can list saved machine learning models and then request detailed performance metrics. This helps data scientists compare schema layers and track changes in prediction quality directly through conversation.

Does Dataiku DSS MCP let me run manual pipeline jobs? +

Absolutely. You can use the tools to list all available pipeline jobs, check their status using get_job, and even trigger a full rebuild or retraining cycle via automation scenarios.

What if I need to audit the SQL logic in my data transformations? +

You can retrieve recipes by listing them first, then using the specific tool to pull the explicit configuration structure. This allows you to verify exact Python or SQL code without opening the DSS interface.

How do I find out what projects I have access to? +

You simply ask your agent to list all accessible DSS projects. It provides a comprehensive overview, including project metadata and tags, so you know exactly what resources are available for your team.