How to Use the Dataiku DSS MCP in CrewAI

Deploy a specialized crew of agents to manage Dataiku DSS pipelines and monitor ML models for autonomous operations.

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Connect Dataiku DSS MCP to CrewAI

Create your Vinkius account to connect Dataiku DSS to CrewAI 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 CrewAI

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Assign Dataiku DSS roles to your CrewAI crew

Give your researchers access to `list_datasets` and `get_project` to gather context. Meanwhile, your operator agent uses `run_scenario` to keep the data moving. They share a memory of what happened in the last run. This prevents the agents from doing redundant work while keeping the pipeline active.

Monitor Dataiku DSS model health with CrewAI

Your monitor agent calls `list_models` and `get_model` on a schedule. It watches for performance dips and notifies your lead agent if a retrain is needed. This creates a self-healing loop. The crew identifies the issue, triggers the scenario, and confirms the fix without you touching a thing.

Sync Dataiku DSS plugins using CrewAI

Use `list_plugins` to audit your environment and ensure all agents are working with the same toolset. It keeps your crew aligned on what capabilities are available. If you add a plugin, the agent sees it immediately. Your crew adjusts its strategy based on the updated tool list.

Setup guide

Set up Dataiku DSS MCP in CrewAI

Prerequisites

Python 3.10+ installed
crewai package (pip install crewai)
Active Vinkius subscription with a valid endpoint token

1

Install CrewAI
Run pip install crewai to install the framework. MCP support is built-in via the mcps parameter.
2

Add the MCP URL to your agent
Pass your Vinkius endpoint directly to the mcps list. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. CrewAI handles tool discovery and caching automatically.
3

Kick off your crew
Create a Crew with your agent and tasks. Call crew.kickoff() — the agent will automatically invoke Dataiku DSS tools as needed.

crew.py

from crewai import Agent, Task, Crew

agent = Agent(
    role="Dataiku DSS Analyst",
    goal="Access and analyze Dataiku DSS data via MCP.",
    backstory="Expert analyst with direct Dataiku DSS access.",
    mcps=[
        "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ],
)

task = Task(
    description="List recent Dataiku DSS transactions",
    agent=agent,
    expected_output="A summary of recent activity",
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

Get your connection token →

Prerequisites

Python 3.10+ installed
crewai + crewai-tools packages
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install crewai crewai-tools. The MCPServerAdapter handles lifecycle management and tool conversion.
2

Connect with MCPServerAdapter
Use MCPServerAdapter as a context manager with SseServerParameters pointing to your Vinkius endpoint. The adapter automatically manages connection lifecycle.
3

Assign tools and run
Pass the returned mcp_tools to your agent's tools parameter. The adapter converts MCP tools to native BaseTool objects compatible with all CrewAI agents.

crew.py

from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
from mcp import SseServerParameters

server_params = SseServerParameters(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

with MCPServerAdapter(server_params) as mcp_tools:
    agent = Agent(
        role="Dataiku DSS Analyst",
        goal="Access and analyze Dataiku DSS data via MCP.",
        backstory="Expert analyst with direct Dataiku DSS access.",
        tools=mcp_tools,
    )

    task = Task(
        description="List recent Dataiku DSS transactions",
        agent=agent,
        expected_output="A summary of recent activity",
    )

    crew = Crew(agents=[agent], tasks=[task])
    result = crew.kickoff()
    print(result)

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 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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Common questions about Dataiku DSS MCP in CrewAI

Pass the Vinkius URL in your Agent definition. The crew will automatically discover the tools and assign them based on their roles.

They can. One agent can list the jobs while another agent analyzes the logs to decide if the pipeline needs a manual intervention.

It works perfectly. You set the order, and the agents pass the results of their tool calls to each other until the task is done.

Vinkius manages the authentication. Your agents only see the tool outputs, not the underlying credentials.

The server limits data exposure to project and model metadata. Your actual training data remains inside your own infrastructure at all times.

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