How to Use the Cocktail API MCP in OpenAI Agents SDK

Build production-grade agents that safely serve up verified drink recipes using OpenAI Agents SDK.

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Connect Cocktail API MCP to OpenAI Agents SDK

Create your Vinkius account to connect Cocktail API 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.

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Setup Cocktail API with OpenAI Agents SDK

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Secure Cocktail API MCP Server agent handoffs

This Cocktail API MCP Server integration lets your production agents route drink queries to specialized mixers without leaking system prompts. When a user asks for a dry martini, OpenAI Agents SDK shifts the task to a designated bartender agent that executes `get_classic_martinis` safely. Tracing on the OpenAI dashboard lets you watch every step of the ingredient audit. If someone inputs a bad ingredient, the built-in guardrails stop the agent before it calls `get_cocktails_by_ingredients` with trash data.

Auto-discovered ingredient auditing

This toolset exposes instant ingredient auditing directly to your active MCP agent pool. The SDK reads the hosted endpoint and immediately exposes `search_cocktails` without requiring manual schema definitions. Setting cacheToolsList to true keeps your API latency low. Your agents instantly pull records via `get_rum_cocktails` or `get_vodka_cocktails` without rebuilding the tool schema on every turn.

Multi-agent recipe validation

This multi-agent setup validates complex drink recipes before they reach your production backend. One curator agent pulls classic sour profiles using `get_classic_margaritas` while a safety checker verifies liquid measurements. By separating these concerns, you prevent your production system from outputting toxic proportions. You get clean, validated drink specs directly from `get_tequila_cocktails` with zero manual intervention.

Setup guide

Set up Cocktail API 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 Cocktail API tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate Cocktail API 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="Cocktail API Agent",
            instructions="You have access to Cocktail API tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Common questions about Cocktail API MCP in OpenAI Agents SDK

Vinkius manages the credentials behind a single endpoint token. You pass this token to MCPServerStreamableHttp, and your agents gain instant, authenticated access to `get_gin_cocktails` without storing raw API keys in your environment.

Yes, you control this at the agent level. Define a specialized agent in Python and only expose `search_cocktails` to it while keeping back-end inventory tools restricted to admin agents.

Caching prevents unnecessary network hops when your agent system boots up. It saves the schema of tools like `get_rum_cocktails` locally, keeping your response times under a second.

Use the SDK's built-in guardrail functions. You write a validation wrapper that inspects the output of `get_cocktails_by_ingredients` before the agent presents the recipe to the end user.

Vinkius runs this MCP server inside an ephemeral V8 sandbox, meaning zero permanent logs of your custom search queries. Your proprietary ingredient lists are processed in memory and wiped immediately after the tools return their results.

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