How to Use the Zenkit MCP in OpenAI Agents SDK

Q: Can I use the Zenkit MCP Server to track my agent’s current environment?

Yep. The getworkspacedetails tool lets your agent pull details about its overall workspace context at any point in the execution flow. It keeps the whole process traceable.

Manage structured data in production agents with OpenAI Agents SDK.

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Connect Zenkit MCP to OpenAI Agents SDK

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

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Read and write list items using the MCP Server

Need to check what's in a list? Your AI client can run `list_entries` to pull all current records. It also lets you populate data by calling `create_entry`. This means your production agent doesn't just talk; it actually writes and modifies structured information. You can also modify existing data with `update_entry`, or clean up old records entirely using `delete_entry`. These tools give the agent full CRUD capabilities on Zenkit lists, making sure your workflow stays accurate.

Discover list structure details for OpenAI Agents SDK

Before writing data, you need to know what fields are available. The `list_elements` tool shows exactly which fields a list uses. Pair that with `get_list_details` to understand the rules of an entire list. It’s crucial context; your agent needs to know its boundaries to operate safely. This set of tools also lets you browse all available workspaces and their associated lists via `list_workspaces`. You get a clear map of where data lives, preventing agents from trying to write records in the wrong place.

Work with workspace context using MCP Server

Sometimes you need big-picture details. The agent can grab full context about where it is by calling `get_workspace_details`. This gives visibility into the overall environment your agent is working in. Want to know what lists exist across the board? Use `list_workspaces` first, then drill down with `get_list_details`. It's how you build reliable, multi-step agents that track their own location and context throughout a process.

Setup guide

Set up Zenkit 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 Zenkit tools at runtime.
3

Create your Agent

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

Run the agent

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

The MCP Server exposes Zenkit's data management tools as functions your agent can call. Your client auto-discovers these capabilities, treating them just like any other specialized action it needs to take.

It manages structured records inside lists and provides details on workspaces. Specifically, you're dealing with list entries, which are JSON objects containing defined field values.

Yep. The `get_workspace_details` tool lets your agent pull details about its overall workspace context at any point in the execution flow. It keeps the whole process traceable.

Because it gives you reliable control over structured data. You aren't guessing; you're calling explicit functions like `create_entry` or `update_entry`, which fits perfectly into a constrained, safe agent architecture.

The server touches 'list entries' data. You must ensure your agents only read or write the necessary fields, especially when using `update_entry`, to maintain strict data integrity.

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