How to Use the Vouchery.io MCP in OpenAI Agents SDK
Build production agents that manage customer discounts and loyalty programs using OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Vouchery.io MCP to OpenAI Agents SDK
Create your Vinkius account to connect Vouchery.io 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.
Manage Vouchery Campaigns
Your agent can list all active marketing campaigns by calling `list_campaigns`. This gives you a clean view of what's running, so you don't have to manually check the dashboard. Need to start something new? Just tell your AI client to use `create_campaign`, giving it a name and type. It handles the setup for you.
Process Voucher Claims
When a customer tries to claim a discount, the agent uses `redeem_voucher`. This function processes the code instantly and reports back on its status. The system also lets your AI client check specific codes with `get_voucher` before running any actions. It's reliable for checking validity.
Track Customer Accounts
If you need to know who bought what, the agent calls `list_customers`. This returns a list of profiles so your system can act on specific people. You can also update or create records using `create_customer`, keeping all customer data current without needing manual database edits.
Set up Vouchery.io 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 Vouchery.io tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Vouchery.io tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Vouchery.io 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="Vouchery.io Agent",
instructions="You have access to Vouchery.io 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 Vouchery.io. 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.
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 Vouchery.io MCP in OpenAI Agents SDK
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