How to Use the NHL MCP in OpenAI Agents SDK

Q: Can I filter NHL player data with OpenAI Agents SDK?

Yes. Use suggestplayers to find IDs and then pass those to getplayerlanding. This helps your agent narrow down specific stats from the league database.

Build production-grade hockey agents using the OpenAI Agents SDK with direct access to live game data.

See Vinkius in Action

Works with every AI agent you already use

…and any MCP-compatible client

MCP Servers - Free for Subscribers

Connect NHL MCP to OpenAI Agents SDK

Create your Vinkius account to connect NHL to OpenAI Agents SDK and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

GDPR Free for Subscribers

Setup NHL with OpenAI Agents SDK

Ask AI about this MCP

ChatGPT

Claude

Perplexity

Real-time game monitoring for OpenAI Agents SDK

Your agent tracks live matchups by invoking `get_live_scores` to pull current game states. It parses official league feeds to keep your backend updated without manual polling. This MCP Server provides raw data objects that your agent handles through its internal guardrails. You define the logic, and the server feeds the precise game facts.

Automated player analysis and stat retrieval

Query specific athlete performance metrics using `get_player_landing` or `get_skater_summary`. Your agent fetches biographical data and seasonal stats to populate your custom reporting tools. Type-safe responses mean your agent receives clean data structures every time. It avoids common parsing errors by relying on the predefined schema for all player queries.

Full schedule management for your agent

Control your workflow by using `get_team_monthly_schedule` to organize future operations. Your agent plans its tasks around specific game dates and times. This setup ensures your agent knows exactly when games happen. It uses `get_schedule_by_date` to handle historical lookups or future planning within your production environment.

Setup guide

Set up NHL MCP in OpenAI Agents SDK

Prerequisites

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

1

Install the SDK

Run pip install openai-agents to install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed.
2

Connect via SSE transport

Use MCPServerSse with your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. The SDK auto-discovers all NHL tools at runtime.
3

Create your Agent

Pass the MCP to Agent(mcp_servers=[server]). The agent receives NHL tools as native definitions — JSON schemas resolve automatically.
4

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate NHL tools and returns structured results. Copy the full example on the right to get started.

agent.py

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

async def main():
    async with MCPServerSse(
        url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
    ) as server:
        agent = Agent(
            name="NHL Agent",
            instructions="You have access to NHL tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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 NHL. 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.

Why Choose Vinkius

Vinkius connects your tools to AI with real-time monitoring and automatic cost savings — all from one dashboard.

Connect NHL now

Real-time monitoring

Live

visibility into every interaction

Connect your favorite tools to your AI and see exactly what's happening — every request, every response, in real time.

Built-in savings

60%

lower AI costs

Vinkius compresses data between your apps and your AI automatically. Lower bills every month — no configuration required.

Single dashboard

One

place for every integration

Every tool your AI connects to, managed from a single screen. One account, complete control.

Common questions about NHL MCP in OpenAI Agents SDK

You connect the server to your agent constructor and call the `get_live_scores` tool. The agent automatically maps the JSON output into your application logic.

Yes. Use `suggest_players` to find IDs and then pass those to `get_player_landing`. This helps your agent narrow down specific stats from the league database.

The server provides direct access to league API endpoints. Your agent processes these responses in real-time to ensure your data stays current.

The server returns standard HTTP status codes for every request. Your agent catches these errors during the execution phase to prevent system crashes.

This server only reads public league statistics. It does not store or process your private user credentials or personal identity records.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

OpenAI Agents SDK sdk-python

Google ADK sdk-python

Pydantic AI sdk-python