How to Use the Jservice MCP in OpenAI Agents SDK
Build production trivia agents with the OpenAI Agents SDK. Your agent gets validated, traceable access to the Jservice database.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Jservice MCP to OpenAI Agents SDK
Create your Vinkius account to connect Jservice 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.
Get Trivia Categories and Clues
The `get_categories` tool pulls a list of Jeopardy! categories your agent can work with. You get up to 100 at a time, so you can quickly populate a game board or give the user options. The `get_category` tool then drills down, fetching all clues for a specific category ID. Once your agent has a category, it can use the `get_clues` tool to find specific questions. Filter by value, date, or offset to build rounds with escalating difficulty. The OpenAI SDK's guardrails mean your agent won't ask for a category that doesn't exist, preventing wasted API calls.
Generate Random Trivia Questions
Use the `get_random_clues` tool to pull a random set of questions for quick-fire trivia rounds. It's perfect for building a chatbot that can drop a trivia question on command without needing a category first. You can request up to 100 clues in a single call. This is where the OpenAI Agents SDK really shines. Your agent can decide when a random question is appropriate, and the framework's tracing gives you a full audit trail. You'll see exactly why it chose `get_random_clues` and what it did with the result, right in the OpenAI dashboard.
Safe Trivia Actions with OpenAI Agents SDK
This Jservice MCP Server isn't just about data; it's about controlled actions. The tools are auto-discovered by your agent, so there's zero setup to map functions. Just point it at the server endpoint and set `cacheToolsList=True` for better performance. Because the SDK validates actions before execution, your agent's behavior stays predictable. If it tries to use `get_clues` with a bad filter, the action is blocked before it ever hits the API. This is critical for a deployed product that can't afford runtime errors.
Set up Jservice MCP in OpenAI Agents SDK
Prerequisites
- Python 3.10+ installed
-
openai-agentspackage (pip install openai-agents) - Active Vinkius subscription with a valid endpoint token
- 1
Install the SDK
Run
pip install openai-agentsto install the OpenAI Agents SDK. The MCP integration is built-in — no extra dependencies needed. - 2
Connect via SSE transport
Use
MCPServerSsewith your Vinkius endpoint URL. Replace[YOUR_TOKEN_HERE]with your token from cloud.vinkius.com. The SDK auto-discovers all Jservice tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Jservice tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Jservice tools and returns structured results. Copy the full example on the right to get started.
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="Jservice Agent",
instructions="You have access to Jservice tools.",
mcp_servers=[server],
)
result = await Runner.run(agent, "List recent transactions")
print(result.final_output)
asyncio.run(main()) Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Jservice. 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 Jservice MCP in OpenAI Agents SDK
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