How to Use the VivifyScrum MCP in OpenAI Agents SDK

Q: How do I manage multiple teams using VivifyScrum and OpenAI Agents SDK?

You call listteams to see all existing groups. The agent can then use that list, combined with listsprints, to focus its work on the right team's current development cycle.

Q: What if I need to update an item using VivifyScrum and OpenAI Agents SDK?

You simply call the updateitem tool. Because you are running this in a production agent system, the guardrails confirm that the provided input matches the expected data structure before the change goes through.

Run complex agile operations with VivifyScrum using OpenAI Agents SDK.

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Connect VivifyScrum MCP to OpenAI Agents SDK

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

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Managing the entire project lifecycle via MCP Server

You can list all available boards and organizations, giving your agent a full view of the portfolio. It's useful for an initial audit run or when you need to identify which projects require attention. Your agent also handles core data management: it lets you `create_item` for new stories and use `update_item` on existing tasks. The built-in guardrails ensure that any changes executed adhere strictly to defined parameters, preventing accidental writes.

Tracking progress with VivifyScrum's worklogs

Need to know who worked on what and when? You can use `get_worklogs` to fetch detailed activity records for a board. This is key for reporting or auditing compliance. Furthermore, the agent allows you to get specific details about any given task using `get_item`. When combined with `list_board_items`, your AI client builds a complete picture of item status and history without needing multiple manual lookups.

Automating resource discovery for OpenAI Agents SDK

The agent can pull general account information via `get_account_info` or list every team within your workspace using `list_teams`. This helps your specialized agents know who they're dealing with. Want to see what hooks are active? It exposes a `list_webhooks` tool. Passing this capability to the agent means it can assess integration points across different systems connected to VivifyScrum.

Setup guide

Set up VivifyScrum 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 VivifyScrum tools at runtime.
3

Create your Agent

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

Run the agent

Call Runner.run(agent, prompt) to execute. The agent invokes the appropriate VivifyScrum 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="VivifyScrum Agent",
            instructions="You have access to VivifyScrum tools.",
            mcp_servers=[server],
        )
        result = await Runner.run(agent, "List recent transactions")
        print(result.final_output)

asyncio.run(main())

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by VivifyScrum. 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.

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Common questions about VivifyScrum MCP in OpenAI Agents SDK

The MCP Server exposes tools that your agent discovers automatically. Your AI client calls the server's functions—like `list_boards` or `create_item`—and the built-in guardrails validate every action before execution.

Absolutely. Your agent can list all organizations, get board details (`get_board`), and then fetch worklogs using `get_worklogs`. The full tracing dashboard lets you see the entire chain of calls.

This MCP Server deals with project metadata, including organizational details, board lists, and specific item descriptions. It handles structured agile project information.

You call `list_teams` to see all existing groups. The agent can then use that list, combined with `list_sprints`, to focus its work on the right team's current development cycle.

You simply call the `update_item` tool. Because you are running this in a production agent system, the guardrails confirm that the provided input matches the expected data structure before the change goes through.

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