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 OpenAI Agents SDK 6 tools — connect in under 2 minutes

Name: DataRobot
Availability: InStock
Author: Vinkius

openai.github.io/openai-agents-python/mcp

Built by Vinkius GDPR 6 Tools SDK

The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect DataRobot through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.

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

import asyncio
from agents import Agent, Runner
from agents.mcp import MCPServerStreamableHttp

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MCPServerStreamableHttp(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as mcp_server:

        agent = Agent(
            name="DataRobot Assistant",
            instructions=(
                "You help users interact with DataRobot. "
                "You have access to 6 tools."
            ),
            mcp_servers=[mcp_server],
        )

        result = await Runner.run(
            agent, "List all available tools from DataRobot"
        )
        print(result.final_output)

asyncio.run(main())

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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.

The OpenAI Agents SDK auto-discovers all 6 tools from DataRobot through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries DataRobot, another analyzes results, and a third generates reports, all orchestrated through Vinkius.

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 OpenAI Agents SDK 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 OpenAI Agents SDK via MCP

Follow these steps to integrate the DataRobot MCP Server with OpenAI Agents SDK.

Install the SDK

Run pip install openai-agents in your Python environment

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Run the script

Save the code above and run it: python agent.py

Explore tools

The agent will automatically discover 6 tools from DataRobot

Why Use OpenAI Agents SDK with the DataRobot MCP Server

OpenAI Agents SDK provides unique advantages when paired with DataRobot through the Model Context Protocol.

Native MCP integration via `MCPServerSse`, pass the URL and the SDK auto-discovers all tools with full type safety

Built-in guardrails, tracing, and handoff patterns let you build production-grade agents without reinventing safety infrastructure

Lightweight and composable: chain multiple agents and MCP servers in a single pipeline with minimal boilerplate

First-party OpenAI support ensures optimal compatibility with GPT models for tool calling and structured output

DataRobot + OpenAI Agents SDK Use Cases

Practical scenarios where OpenAI Agents SDK combined with the DataRobot MCP Server delivers measurable value.

Automated workflows: build agents that query DataRobot, process the data, and trigger follow-up actions autonomously

Multi-agent orchestration: create specialist agents. one queries DataRobot, another analyzes results, a third generates reports

Data enrichment pipelines: stream data through DataRobot tools and transform it with OpenAI models in a single async loop

Customer support bots: agents query DataRobot to resolve tickets, look up records, and update statuses without human intervention

DataRobot MCP Tools for OpenAI Agents SDK (6)

These 6 tools become available when you connect DataRobot to OpenAI Agents SDK 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 OpenAI Agents SDK

Ready-to-use prompts you can give your OpenAI Agents SDK 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 OpenAI Agents SDK

Common issues when connecting DataRobot to OpenAI Agents SDK through the Vinkius, and how to resolve them.

MCPServerStreamableHttp not found

Ensure you have the latest version: pip install --upgrade openai-agents

Agent not calling tools

Make sure your prompt explicitly references the task the tools can help with.

DataRobot + OpenAI Agents SDK FAQ

Common questions about integrating DataRobot MCP Server with OpenAI Agents SDK.

How does the OpenAI Agents SDK connect to MCP?

Use MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.