Can my agent list all models within a specific DataRobot project?

Yes. Use the 'list_models' tool and provide the project ID. The agent will enumerate the explicit bounded layers and AI configurations stored directly in the DataRobot platform, allowing you to compare models through the chat.

How do I retrieve training metrics for a specific model via chat?

Provide the project ID and model ID to the 'get_model' tool. Your agent will retrieve the discrete logical properties and natively export raw training metrics within your mapped ML structures accurately.

Can I monitor active cloud deployments through the agent?

Absolutely. Use the 'list_deployments' tool. Your agent will intercept precise global configurations tracing executed DataRobot nodes deployed natively into scalable clouds, giving you real-time visibility into your production AI.

DataRobot MCP Server for Google ADK 6 tools — connect in under 2 minutes

Name: DataRobot
Availability: InStock
Author: Vinkius

google.github.io/adk-docs/tools/mcp-tools

Built by Vinkius GDPR 6 Tools SDK

Google Agent Development Kit (ADK) is Google's framework for building production AI agents. Add DataRobot as an MCP tool provider through Vinkius and your ADK agents can call every tool with full schema introspection.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

from google.adk.agents import Agent
from google.adk.tools.mcp_tool import McpToolset
from google.adk.tools.mcp_tool.mcp_session_manager import (
    StreamableHTTPConnectionParams,
)

# Your Vinkius token. get it at cloud.vinkius.com
mcp_tools = McpToolset(
    connection_params=StreamableHTTPConnectionParams(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
    )
)

agent = Agent(
    model="gemini-2.5-pro",
    name="datarobot_agent",
    instruction=(
        "You help users interact with DataRobot "
        "using 6 available tools."
    ),
    tools=[mcp_tools],
)

Fully ManagedVinkius Servers

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High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About DataRobot MCP Server

Connect your DataRobot account to any AI agent and take full control of your automated machine learning and AI lifecycle management through natural conversation.

Google ADK natively supports DataRobot as an MCP tool provider. declare Vinkius Edge URL and the framework handles discovery, validation, and execution automatically. Combine 6 tools with Gemini's long-context reasoning for complex multi-tool workflows, with production-ready session management and evaluation built in.

What you can do

Project & Workspace Auditing — List and retrieve exact nested elements from DataRobot projects to identify physical boundaries isolated in your workspace
Model Performance Monitoring — Enumerate explicit bounded layers and retrieve discrete logical properties natively exporting raw training metrics
Deployment Management — Intercept precise global configurations tracing executed DataRobot nodes deployed natively into scalable clouds
Dataset Extraction — Inspect raw metrics executing global data extractions routing exact DataRobot bounds securely mapped logically
ML Lifecycle Oversight — Monitor AI configurations stored directly in current platforms and audit specific model versioning

The DataRobot MCP Server exposes 6 tools through the Vinkius. Connect it to Google ADK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect DataRobot to Google ADK via MCP

Follow these steps to integrate the DataRobot MCP Server with Google ADK.

Install Google ADK

Run pip install google-adk

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Create the agent

Save the code above and integrate into your ADK workflow

Explore tools

The agent will discover 6 tools from DataRobot via MCP

Why Use Google ADK with the DataRobot MCP Server

Google ADK provides unique advantages when paired with DataRobot through the Model Context Protocol.

Google ADK natively supports MCP tool servers. declare a tool provider and the framework handles discovery, validation, and execution

Built on Gemini models, ADK provides long-context reasoning ideal for complex multi-tool workflows with DataRobot

Production-ready features like session management, evaluation, and deployment come built-in. not bolted on

Seamless integration with Google Cloud services means you can combine DataRobot tools with BigQuery, Vertex AI, and Cloud Functions

DataRobot + Google ADK Use Cases

Practical scenarios where Google ADK combined with the DataRobot MCP Server delivers measurable value.

Enterprise data agents: ADK agents query DataRobot and cross-reference results with internal databases for comprehensive analysis

Multi-modal workflows: combine DataRobot tool responses with Gemini's vision and language capabilities in a single agent

Automated compliance checks: schedule ADK agents to query DataRobot regularly and flag policy violations or configuration drift

Internal tool platforms: build self-service agent platforms where teams connect their own MCP servers including DataRobot

DataRobot MCP Tools for Google ADK (6)

These 6 tools become available when you connect DataRobot to Google ADK via MCP:

get_model

Get model

get_project

Get project

list_datasets

List datasets

list_deployments

List deployments

list_models

List models

list_projects

List projects

Example Prompts for DataRobot in Google ADK

Ready-to-use prompts you can give your Google ADK agent to start working with DataRobot immediately.

"List all projects in my DataRobot workspace"

"Show me the top models for project 'abc-123'"

"List all active deployments in production"

Troubleshooting DataRobot MCP Server with Google ADK

Common issues when connecting DataRobot to Google ADK through the Vinkius, and how to resolve them.

McpToolset not found

Update: pip install --upgrade google-adk

DataRobot + Google ADK FAQ

Common questions about integrating DataRobot MCP Server with Google ADK.

How does Google ADK connect to MCP servers?

Import the MCP toolset class and pass the server URL. ADK discovers and registers all tools automatically, making them available to your agent's tool-use loop.

Can ADK agents use multiple MCP servers?

Yes. Declare multiple MCP tool providers in your agent configuration. ADK merges all tool schemas and the agent can call tools from any server in a single turn.

Which Gemini models work best with MCP tools?

Gemini 2.0 Flash and Pro models both support function calling required for MCP tools. Flash is recommended for latency-sensitive use cases, Pro for complex reasoning.