How to Use the Armano MCP in OpenAI Agents SDK

Q: How do I connect the Armano MCP Server to my OpenAI Agents SDK pipeline?

Install the SDK with pip install openai-agents and initialize the server using MCPServerStreamableHttp with your Vinkius endpoint. Pass the server instance into your agent's mcpservers list to auto-discover all ten tools.

Q: What is the benefit of caching the Armano MCP Server tool list?

Setting cacheToolsList=True in your SDK configuration reduces startup latency. Your agent skips the initial discovery handshake on subsequent runs, speeding up time-tracking and employee lookups.

Run production-grade OpenAI Agents SDK workflows that directly manage your team's timesheets and project data in Armano.

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Connect Armano MCP to OpenAI Agents SDK

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

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Automate timesheet audits with OpenAI Agents SDK

The `list_time_entries` and `get_time_entry` tools let your OpenAI agent pull raw timesheet data directly into its execution loop. Since you are building in production, the SDK applies guardrails to verify hours against your policies before passing data to downstream systems. Your agent uses these tools to flag anomalies in hours worked without manual supervision. By caching the tools list in your Python setup, the agent instantly accesses the Armano schema, running audits across hundreds of records while maintaining full tracing in your OpenAI dashboard.

Secure employee and project lookups via MCP Server

The `get_employee` and `get_project` tools expose secure endpoints for your agent to query internal organizational structures. This MCP Server integration allows specialized agents to hand off tasks between each other when resolving complex payroll or staffing inquiries. When an agent needs to map a project budget to an employee, it queries the server using these tools. The SDK's built-in safety constraints ensure the agent only accesses authorized records, preventing unauthorized data exposure during multi-agent handoffs.

Track project progress and leave requests automatically

The `list_projects` and `list_leaves` tools provide real-time visibility into project timelines and employee availability. Your agent queries these endpoints to update resource schedules without manual data entry. By combining these tools with OpenAI's native tools routing, the agent schedules project tasks based on actual team availability. If a developer has an active leave request, the agent routes the task to an active team member instead.

Setup guide

Set up Armano 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 Armano tools at runtime.
3

Create your Agent

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

Run the agent

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

Install the SDK with `pip install openai-agents` and initialize the server using `MCPServerStreamableHttp` with your Vinkius endpoint. Pass the server instance into your agent's `mcp_servers` list to auto-discover all ten tools.

Yes, you can control tool access by setting up specialized agents with specific system instructions or by filtering the tools list before passing it to the agent constructor. This prevents an agent from accidentally triggering tools like `create_time_entry` when it only needs read access.

The SDK relies on your connection configuration to handle API limits. You can monitor every call to `check_armano_status` or timesheet queries directly inside your OpenAI developer dashboard tracing view.

Setting `cacheToolsList=True` in your SDK configuration reduces startup latency. Your agent skips the initial discovery handshake on subsequent runs, speeding up time-tracking and employee lookups.

Vinkius runs the server in an isolated V8 sandbox, meaning employee records and time entries are never stored on our servers. Your API keys are encrypted, and data flows directly between OpenAI and your endpoints over secure transport.

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