How to Use the BigOven MCP in OpenAI Agents SDK

Q: How does the BigOven server handle agent handoffs in OpenAI Agents SDK?

The SDK routes tool outputs like searchrecipes from a search-specialist agent to a meal-planning agent. Each agent maintains its own guardrails while sharing the underlying connection.

Build production culinary agents with OpenAI Agents SDK and the BigOven MCP Server to query over a million recipes safely.

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Connect BigOven MCP to OpenAI Agents SDK

Create your Vinkius account to connect BigOven 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 BigOven with OpenAI Agents SDK

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Safe Recipe Lookups with OpenAI Agents SDK

By calling the `get_recipe` tool, your agent pulls complete preparation steps, ingredient quantities, and cooking times directly from the database into your agent's context. Your system runs these calls through built-in guardrails, verifying the payload structure before execution to ensure no corrupted data breaks your pipeline. If a user asks for a dietary modification, the agent triggers `get_recipe_reviews` to check how other home cooks altered the dish. The SDK handles the handoff between your search agent and your analysis agent without losing the original context.

Intelligent Ingredient-Based Search

Running the `search_by_ingredient` tool matches leftover items or specific pantry ingredients to viable dishes in the database. Your agent processes these results in real time, filtering out unwanted matches before presenting options to the user. When users have complex dietary restrictions, your system chains this with `list_categories` to restrict the search space. You track the entire execution path on your OpenAI dashboard to debug prompt performance instantly.

Seasonal Collection Discovery

With the `list_collections` tool, you fetch curated lists of recipes grouped by season, holiday, or culinary theme. This MCP Server exposes these lists directly to your agent, allowing it to recommend relevant menus dynamically. Once your agent selects a collection, it uses `get_collection` to extract the individual recipe IDs and details. The SDK keeps these operations secure and fast by caching the tool definitions locally.

Setup guide

Set up BigOven 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 BigOven tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate BigOven 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="BigOven Agent",
            instructions="You have access to BigOven 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 BigOven MCP in OpenAI Agents SDK

Install the package and configure the HTTP streamable server using the Vinkius endpoint. Pass the server instance directly into your Agent constructor to let your agent auto-discover all eight tools.

Yes, you manage tool access directly in your agent definition by filtering the discovered tools list. If you only want your agent to read reviews, expose only `get_recipe_reviews` and omit the rest.

The SDK routes tool outputs like `search_recipes` from a search-specialist agent to a meal-planning agent. Each agent maintains its own guardrails while sharing the underlying connection.

The server sends structured data that your agent parses systematically. You should set up system prompts that instruct the model to summarize or paginate the results.

This MCP connection runs in an isolated V8 sandbox on Vinkius. All recipe search keywords, ingredient lists, and collection requests pass through without leaving raw query logs behind, keeping search history confidential.

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