How to Use the Zenedu MCP in OpenAI Agents SDK
Manage your messenger bots and data streams using OpenAI Agents SDK.
Works with every AI agent you already use
…and any MCP-compatible client
Connect Zenedu MCP to OpenAI Agents SDK
Create your Vinkius account to connect Zenedu 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.
Discover all active messaging bots with the MCP Server.
The `list_bots` tool gives you a full roster of every bot running in your system. You get direct access to the names and IDs needed to manage them through your agent workflow. This lets your OpenAI Agents SDK quickly map out which communication channels are available, preventing misconfigurations before they hit production.
Track customer funnels and offers with the MCP Server.
You can run `list_bot_funnels` to see exactly how your bots guide users through conversion pathways. It also lets you pull `list_bot_offers`, showing what specific deals are attached to those paths. Your agent uses this data to build logic—if a user hits Funnel X, it knows they are eligible for Offer Y.
Retrieve subscriber and order records using the MCP Server.
The `list_bot_subscribers` tool pulls a current list of all users interacting with your bots. Pair that up with `list_bot_orders` to get transaction history tied directly to specific user accounts. Your agent can now build reports: Who subscribed, and what did they buy? All validated before execution.
Set up Zenedu 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 Zenedu tools at runtime. - 3
Create your Agent
Pass the MCP to
Agent(mcp_servers=[server]). The agent receives Zenedu tools as native definitions — JSON schemas resolve automatically. - 4
Run the agent
Call
Runner.run(agent, prompt)to execute. The agent invokes the appropriate Zenedu 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="Zenedu Agent",
instructions="You have access to Zenedu 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 Zenedu. 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 Zenedu MCP in OpenAI Agents SDK
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