ReciPal MCP Server for OpenAI Agents SDK 4 tools — connect in under 2 minutes
The OpenAI Agents SDK enables production-grade agent workflows in Python. Connect ReciPal through Vinkius and your agents gain typed, auto-discovered tools with built-in guardrails. no manual schema definitions required.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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="ReciPal Assistant",
instructions=(
"You help users interact with ReciPal. "
"You have access to 4 tools."
),
mcp_servers=[mcp_server],
)
result = await Runner.run(
agent, "List all available tools from ReciPal"
)
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 ReciPal MCP Server
Empower your AI agent to orchestrate your entire food manufacturing and recipe auditing workflow with ReciPal, the specialized source for nutritional labeling data. By connecting ReciPal to your agent, you transform complex ingredient analysis into a natural conversation. Your agent can instantly retrieve recipe details, audit calorie counts, and query ingredient lists without you ever touching a labeling portal. Whether you are conducting product research or managing regional dietary constraints, your agent acts as a real-time nutritional consultant, ensuring your data is always verified and precise.
The OpenAI Agents SDK auto-discovers all 4 tools from ReciPal through native MCP integration. Build agents with built-in guardrails, tracing, and handoff patterns. chain multiple agents where one queries ReciPal, another analyzes results, and a third generates reports, all orchestrated through Vinkius.
What you can do
- Recipe Auditing — Retrieve high-resolution details for all recipes in your catalog, including names, calorie counts, and serving metadata.
- Ingredient Oversight — Audit the available ingredients in the ReciPal database to understand the thematic distribution of components instantly.
- Nutritional Intelligence — Query full nutritional breakdowns for specific recipes to assist in deep-dive dietary classification.
- Resource Discovery — Retrieve unique recipe identifiers to help you identify relevant markers for your food products.
- Operational Monitoring — Check API status to ensure your nutritional research workflow is always operational.
The ReciPal MCP Server exposes 4 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.
How to Connect ReciPal to OpenAI Agents SDK via MCP
Follow these steps to integrate the ReciPal MCP Server with OpenAI Agents SDK.
Install the SDK
Run pip install openai-agents in your Python environment
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com
Run the script
Save the code above and run it: python agent.py
Explore tools
The agent will automatically discover 4 tools from ReciPal
Why Use OpenAI Agents SDK with the ReciPal MCP Server
OpenAI Agents SDK provides unique advantages when paired with ReciPal 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
ReciPal + OpenAI Agents SDK Use Cases
Practical scenarios where OpenAI Agents SDK combined with the ReciPal MCP Server delivers measurable value.
Automated workflows: build agents that query ReciPal, process the data, and trigger follow-up actions autonomously
Multi-agent orchestration: create specialist agents. one queries ReciPal, another analyzes results, a third generates reports
Data enrichment pipelines: stream data through ReciPal tools and transform it with OpenAI models in a single async loop
Customer support bots: agents query ReciPal to resolve tickets, look up records, and update statuses without human intervention
ReciPal MCP Tools for OpenAI Agents SDK (4)
These 4 tools become available when you connect ReciPal to OpenAI Agents SDK via MCP:
check_api_status
Check if the ReciPal service is operational
get_recipe_details
Get full nutritional and ingredient details for a specific recipe by ID
list_recipal_ingredients
List all ingredients available in the ReciPal database
list_recipal_recipes
List all recipes in your ReciPal account
Example Prompts for ReciPal in OpenAI Agents SDK
Ready-to-use prompts you can give your OpenAI Agents SDK agent to start working with ReciPal immediately.
"List all my recipes using ReciPal."
"What are the details for recipe ID '12345'?"
"List all ingredients available in ReciPal."
Troubleshooting ReciPal MCP Server with OpenAI Agents SDK
Common issues when connecting ReciPal to OpenAI Agents SDK through the Vinkius, and how to resolve them.
MCPServerStreamableHttp not found
pip install --upgrade openai-agentsAgent not calling tools
ReciPal + OpenAI Agents SDK FAQ
Common questions about integrating ReciPal 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.Does the SDK support streaming responses?
Connect ReciPal with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect ReciPal to OpenAI Agents SDK
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.
