Arize AI MCP Server for OpenAI Agents SDKGive OpenAI Agents SDK instant access to 6 tools to Create Dataset, Get Model, List Datasets, and more
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect Arize AI through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
Ask AI about this App Connector for OpenAI Agents SDK
The Arize AI app connector for OpenAI Agents SDK is a standout in the Friends Mcp category — giving your AI agent 6 tools to work with, ready to go from day one.
Vinkius delivers Streamable HTTP and SSE to any MCP client
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="Arize AI Assistant",
instructions=(
"You help users interact with Arize AI. "
"You have access to 6 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from Arize AI"
)
print(result.final_output)
asyncio.run(main())
* 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 Arize AI MCP Server
Connect your Arize AI account to any AI agent and take full control of your machine learning observability and automated model monitoring workflows through natural conversation.
The OpenAI Agents SDK auto-discovers all 6 tools from Arize AI through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries Arize AI, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- Project & Trace Orchestration — List and monitor active ML tracing projects programmatically, retrieving detailed high-fidelity execution spans and telemetry data in real-time
- Dataset Lifecycle Management — Programmatically create and manage datasets for model evaluation and validation to maintain a perfectly coordinated ML infrastructure
- Experiment Monitoring — Access and track ML experiments to understand high-fidelity model performance, drift, and data quality across different environments
- Model Intelligence Discovery — Retrieve detailed metadata for specific ML models to coordinate your organizational AI strategy directly through your agent
- Operational Monitoring — Access account-level settings and verify API connectivity directly through your agent for instant performance reporting
The Arize AI 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.
All 6 Arize AI tools available for OpenAI Agents SDK
When OpenAI Agents SDK connects to Arize AI through Vinkius, your AI agent gets direct access to every tool listed below — spanning ml-observability, model-monitoring, data-drift, and more. Every call is secured with network, filesystem, subprocess, and code evaluation entitlements inside a sandboxed runtime. Beyond a simple connection, you get a full AI Gateway with real-time visibility into agent activity, enterprise governance, and optimized token usage.
Create a dataset
Get model details
List datasets
List experiments
List projects
List spans
Connect Arize AI to OpenAI Agents SDK via MCP
Follow these steps to wire Arize AI into OpenAI Agents SDK. The entire setup takes under two minutes — your credentials stay safe behind the Vinkius.
Install the SDK
pip install openai-agents in your Python environmentReplace the token
[YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.comRun the script
python agent.pyExplore tools
Why Use OpenAI Agents SDK with the Arize AI MCP Server
OpenAI Agents SDK provides unique advantages when paired with Arize AI 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
Arize AI + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the Arize AI MCP Server delivers measurable value.
Automated workflows: build agents that query Arize AI, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries Arize AI, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through Arize AI tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query Arize AI to resolve tickets, look up records, and update statuses without human intervention
Example Prompts for Arize AI in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with Arize AI immediately.
"List all active ML projects in my Arize account."
"Show the recent execution spans for project '1024'."
"Create a new dataset 'Q2_Eval_Data' for model evaluation."
Troubleshooting Arize AI MCP Server with OpenAI Agents SDK
Common issues when connecting Arize AI to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
Arize AI + OpenAI Agents SDK FAQ
Common questions about integrating Arize AI MCP Server with OpenAI Agents SDK.
How does the OpenAI Agents SDK connect to MCP?
MCPServerSse(url=...) to create a server connection. The SDK auto-discovers all tools and makes them available to your agent with full type information.Can I use multiple MCP servers in one agent?
MCPServerSse instances to the agent constructor. The agent can use tools from all connected servers within a single run.